ArticleBMC bioinformatics2010
Systematic integration of experimental data and models in systems biology.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Neural network based integration of assays to assess pathogenic potential.Scientific reports · 2023Article
- Structural Thermokinetic Modelling.Metabolites · 2022Article
- SBML Level 3: an extensible format for the exchange and reuse of biological models.Molecular systems biology · 2020Review
- STRENDA DB: enabling the validation and sharing of enzyme kinetics data.The FEBS journal · 2018Article
- SBMLmod: a Python-based web application and web service for efficient data integration and model simulation.BMC bioinformatics · 2017Article
- libChEBI: an API for accessing the ChEBI database.Journal of cheminformatics · 2016Article
- How to make Mathematics Biology's next and better microscope.Biomolecular detection and quantification · 2014Article
- Path2Models: large-scale generation of computational models from biochemical pathway maps.BMC systems biology · 2013Article
- A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes.FEBS letters · 2013Article
- An analysis of a 'community-driven' reconstruction of the human metabolic network.Metabolomics : Official journal of the Metabolomic Society · 2013Article
- Article
- Condor-COPASI: high-throughput computing for biochemical networks.BMC systems biology · 2012Article
- Enzyme informatics.Current topics in medicinal chemistry · 2012Review
- Reproducible computational biology experiments with SED-ML--the Simulation Experiment Description Markup Language.BMC systems biology · 2011Article
- Software that goes with the flow in systems biology.BMC biology · 2010Article
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
backgroundThe behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources.
resultsTaverna workflows have been developed for the automated assembly of quantitative parameterised metabolic networks in the Systems Biology Markup Language (SBML). A SBML model is built in a systematic fashion by the workflows which starts with the construction of a qualitative network using data from a MIRIAM-compliant genome-scale model of yeast metabolism. This is followed by parameterisation of the SBML model with experimental data from two repositories, the SABIO-RK enzyme kinetics database and a database of quantitative experimental results. The models are then calibrated and simulated in workflows that call out to COPASIWS, the web service interface to the COPASI software application for analysing biochemical networks. These systems biology workflows were evaluated for their ability to construct a parameterised model of yeast glycolysis.
conclusionsDistributed information about metabolic reactions that have been described to MIRIAM standards enables the automated assembly of quantitative systems biology models of metabolic networks based on user-defined criteria. Such data integration processes can be implemented as Taverna workflows to provide a rapid overview of the components and their relationships within a biochemical system.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.