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Resources for integrative systems biology: from data through databases to networks and dynamic system models.

Aylwin Ng·Borisas Bursteinas·Qiong Gao·Ewan Mollison·Marketa Zvelebil
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Abstract

In systems biology, biologically relevant quantitative modelling of physiological processes requires the integration of experimental data from diverse sources. Recent developments in high-throughput methodologies enable the analysis of the transcriptome, proteome, interactome, metabolome and phenome on a previously unprecedented scale, thus contributing to the deluge of experimental data held in numerous public databases. In this review, we describe some of the databases and simulation tools that are relevant to systems biology and discuss a number of key issues affecting data integration and the challenges these pose to systems-level research.

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AnimalsComputer SimulationData CollectionDatabases, GeneticGene ExpressionGenomicsHumansMetabolic Networks and PathwaysModels, BiologicalModels, MolecularPhenotypeProteomicsSoftwareSystems BiologyJournal ArticleReview

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Aylwin Ng, Borisas Bursteinas, Qiong Gao, Ewan Mollison, Marketa Zvelebil. 2006-10-13. Resources for integrative systems biology: from data through databases to networks and dynamic system models.. https://doi.org/10.1093/bib%2Fbbl036

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