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

by: A Ng, B Bursteinas, Q Gao, E Mollison, M Zvelebil

Brief Bioinform, Vol. 7, No. 4. (December 2006), pp. 318-330.

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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.

@article{citeulike:1314226, 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.}, address = {Bioinformatics and Systems Biology Group, Ludwig Institute for Cancer Research, University College London Branch, 91 Riding House Street, London W1W 7BS, UK.}, author = {Ng, A. and Bursteinas, B. and Gao, Q. and Mollison, E. and Zvelebil, M. }, citeulike-article-id = {1314226}, doi = {http://dx.doi.org/10.1093/bib/bbl036}, issn = {1467-5463}, journal = {Brief Bioinform}, keywords = {new, sysbio}, month = {December}, number = {4}, pages = {318--330}, posted-at = {2008-04-10 11:19:31}, priority = {2}, title = {Resources for integrative systems biology: from data through databases to networks and dynamic system models.}, url = {http://dx.doi.org/10.1093/bib/bbl036}, volume = {7}, year = {2006} }

RIS record

TY - JOUR ID - citeulike:1314226 L3 - citeulike-article-id:1314226 TI - Resources for integrative systems biology: from data through databases to networks and dynamic system models. JF - Brief Bioinform VL - 7 IS - 4 SP - 318 EP - 330 AD - Bioinformatics and Systems Biology Group, Ludwig Institute for Cancer Research, University College London Branch, 91 Riding House Street, London W1W 7BS, UK. SN - 1467-5463 N2 - 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. KW - new KW - sysbio AU - Ng, A AU - Bursteinas, B AU - Gao, Q AU - Mollison, E AU - Zvelebil, M PY - 2006/12// UR - http://dx.doi.org/10.1093/bib/bbl036 ER -

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