Literature DB >> 12788544

On the complete determination of biological systems.

Douglas W Selinger1, Matthew A Wright, George M Church.   

Abstract

The nascent field of systems biology ambitiously proposes to integrate information from large-scale biology projects to create computational models that are, in some sense, complete. However, the details of what would constitute a complete systems-level model of an organism are far from clear. To provide a framework for this difficult question it is useful to define a model as a set of rules that maps a set of inputs (e.g. descriptions of the cell's environment) to a set of outputs (e.g. the concentrations of all its RNAs and proteins). We show how the properties of a model affect the required experimental sampling and estimate the number of experiments needed to "complete" a particular model. Based on these estimates, we suggest that the complete determination of a biological system is a concrete, achievable goal.

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Year:  2003        PMID: 12788544     DOI: 10.1016/S0167-7799(03)00113-6

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN: 0167-7799            Impact factor:   19.536


  9 in total

Review 1.  Systems interface biology.

Authors:  Francis J Doyle; Jörg Stelling
Journal:  J R Soc Interface       Date:  2006-10-22       Impact factor: 4.118

2.  The global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states.

Authors:  Christian L Barrett; Christopher D Herring; Jennifer L Reed; Bernhard O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2005-12-15       Impact factor: 11.205

3.  A regulatory network modeled from wild-type gene expression data guides functional predictions in Caenorhabditis elegans development.

Authors:  Brandilyn Stigler; Helen M Chamberlin
Journal:  BMC Syst Biol       Date:  2012-06-26

4.  Toxicity assays in nanodrops combining bioassay and morphometric endpoints.

Authors:  Frédéric Lemaire; Céline A Mandon; Julien Reboud; Alexandre Papine; Jesus Angulo; Hervé Pointu; Chantal Diaz-Latoud; Christian Lajaunie; François Chatelain; André-Patrick Arrigo; Béatrice Schaack
Journal:  PLoS One       Date:  2007-01-17       Impact factor: 3.240

5.  From systems biology to synthetic biology.

Authors:  George M Church
Journal:  Mol Syst Biol       Date:  2005-03-29       Impact factor: 11.429

6.  Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction.

Authors:  Edward J O'Brien; Joshua A Lerman; Roger L Chang; Daniel R Hyduke; Bernhard Ø Palsson
Journal:  Mol Syst Biol       Date:  2013-10-01       Impact factor: 11.429

Review 7.  Toward engineering synthetic microbial metabolism.

Authors:  George H McArthur; Stephen S Fong
Journal:  J Biomed Biotechnol       Date:  2009-12-14

8.  A predictor for predicting Escherichia coli transcriptome and the effects of gene perturbations.

Authors:  Maurice H T Ling; Chueh Loo Poh
Journal:  BMC Bioinformatics       Date:  2014-05-13       Impact factor: 3.169

9.  Unraveling the Complexity of Amyotrophic Lateral Sclerosis Survival Prediction.

Authors:  Stephen R Pfohl; Renaid B Kim; Grant S Coan; Cassie S Mitchell
Journal:  Front Neuroinform       Date:  2018-06-14       Impact factor: 4.081

  9 in total

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