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This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

ELIXIR is about integration of diverse resources including tools, training materials and technical services. Within EXCELERATE, ELIXIR is building portals to collate information on tools and data services (bio.tools), training events and material (TeSS, WP11 e-learning environment), compute resources (WP4 technical service registry) and cross-linked policy, standards and databases (FAIRsharing, WP4). A focus of EXCELERATE is to set up these portals such that they can interoperate.

Currently, a scientist can use TeSS to find training events and materials and then, in a separate search, use bio.tools to find relevant tools, and FAIRsharing to find standards and databases. At the moment these ELIXIR portals provide a useful, but fragmented service.  Ideally, linking TeSS and bio.tools to ELIXIR’s computer resources via common workflow diagrams would enable end-users to discover and learn about the prevalent bioinformatics workflows. In this implementation study, we want to achieve the first step and link TeSS and bio.tools via most prevalent bioinformatics workflows and lay the foundation to later incorporate other ELIXIR platforms, such as the compute resources, to provide an even more useful service for the researcher.

The goal of this implementation study is to provide the life-scientist end-user with a powerful tool to find and use ELIXIR resources - across the spectrum - based on intuitive graphical diagrams of the most prevalent scientific workflows.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

Metabolomics aims to provide novel insights into the biochemical reactions of organisms by characterising the presence and concentrations of low molecular weight compounds from biological samples. The primary analytical tools for such high-throughput data collection are mass spectrometry (MS), often preceded by chromatographic or electrophoretic separation technologies, and nuclear magnetic resonance spectroscopy (NMR).

These technologies produce relatively large and complex data sets that require bioinformaticians, cheminformaticians, biostatisticians, data scientists and computer scientists. Together they develop and apply a wide range of algorithms, software tools, repositories and computational resources to process, analyse, report and store the data and metadata.

Increasingly, insights from genomics, epigenomics, transcriptomics, proteomics/protein interactomics and metabolomics are combined, to gain insights into the dynamics of biological processes. Metabolomics activities are well represented within Europe and ELIXIR nodes. Metabolite identification is the area that the community believes will have maximal impact of computational metabolomics and metabolomics data management and will benefit most from interactions with the existing five ELIXIR platforms and where progress will contribute most to other ELIXIR communities.

The progress through this integrative Implementation Study will benefit industry and academia alike as metabolite identification is one of the major bottlenecks in metabolomics and resolving this challenge requires a community effort.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.

This Metabolomics Community-led project on the standardization of fluxomics workflows aims at:

• establishing standards for isotopic labeling data deposition, a major fluxomics input, and accordingly extending MetaboLights (EMBL-EBI), the reference database for quantitative metabolomic datasets;
• establishing interoperability among largely-used fluxomic tools, building upon the PhenoMeNal fluxomic tool inventory,
• extending BioSchemas to metabolic reactions and their dynamics, using the metabolic reaction database Rhea (SIB) for metabolic model reconstruction,
• containerizing the fluxomic workflow for use in cloud-based environment, and
• standardizing the fluxomics training. The study is aligned with the Human Data and Plant Science Use Cases and the existing Proteomics, Galaxy and the suggested Toxicology, Nutrition and Microbial Biotechnology Communities.

Background

Metabolic reaction rates (fluxes) provide a measure of the in vivo enzymatic activities that cannot be directly available from the transcriptomic, proteomic or metabolomic data alone, even extended with isotopic labeling measurements.

However, flux distribution maps and through them, metabolic network dynamics, can be revealed when analyzing these data integrated with regulatory information using multi-level and multi-scale models. In this context, fluxomics is an integral part of the bioinformatics and systems biology toolbox. It has significant applications in industrial biotechnology, metabolic or protein engineering, nutritional systems biology, toxicology, precision agriculture and crop improvement and network and systems medicine for the investigation of (patho)physiological mechanisms of complex diseases.

A successful fluxomic analysis is based on the accuracy of quantitative metabolomic data (extra- and intra-cellular) and isotopic labeling measurements and the reconstruction of metabolic networks that describe the stoichiometry - and when available the regulation- of metabolic reactions. To date, the community lacks standardized isotopic labeling data repositories, interoperability among the fluxomic tools and harmonized fluxomic training workflows. In this context, the Metabolomics Community decided to focus its second implementation study on the standardization of fluxomic workflows.

Goals

Standardization of the fluxomic workflow requires (a) standardization and FAIRification of the quantitative metabolomic and isotopic labeling data input, (b) standardized reconstruction of metabolic models, based on metabolic reaction databases and ontologies, extended with regulatory information, and (c) interoperability of the various fluxomics tools and the metabolomic and ontology databases. The standardized workflow could be containerized to work in a cloud-based environment. In this implementation study, these objectives will be pursued through the following specific aims:

1. To establish standard rules for the deposition of isotopic labeling data and accordingly extend the MetaboLights database (EMBL-EBI), established as the reference repository for quantitative metabolomic data. This work will build upon ongoing efforts at EBI and ES node in collaboration with the Data, Tools and Interoperability Platforms.
2. To identify largely used fluxomic tools and establish their interoperability, building upon the PhenoMeNal fluxomic tool inventory, in collaboration with the ELIXIR Tools and Interoperability platforms. This implementation study will focus exclusively on open source software, in alignment with the general recommendations of ELIXIR.
3. To establish interoperability between the databases (quantitative metabolomic and isotopic labeling, metabolic reaction, ontologies, protein, signaling networks) and the fluxomic tools for the accurate reconstruction of relevant metabolic models, and to extend BioSchemas to metabolic reactions and their dynamics, in collaboration with the Interoperability platform. Rhea (SIB), to be linked to UniProt by the end of 2018, will be used as the reference metabolic reaction information resource.
4. To containerize the standardized fluxomic workflow for use in cloud-based environment in interaction with the Compute platform.
5. To standardize the fluxomic training workflow and organize webinars and a summer school based on the guidelines and best practices as described in the ELIXIR Training Toolkit, in close collaboration with the Training platform.