@article{14ea7e97c2a34439a8050e8f47645421,
title = "Integrating high-throughput and computational data elucidates bacterial networks",
abstract = "The flood of high-throughput biological data has led to the expectation that computational (or in silico) models can be used to direct biological discovery, enabling biologists to reconcile heterogeneous data types, find inconsistencies and systematically generate hypotheses. Such a process is fundamentally iterative, where each iteration involves making model predictions, obtaining experimental data, reconciling the predicted outcomes with experimental ones, and using discrepancies to update the in silico model. Here we have reconstructed, on the basis of information derived from literature and databases, the first integrated genome-scale computational model of a transcriptional regulatory and metabolic network. The model accounts for 1,010 genes in Escherichia coli, including 104 regulatory genes whose products together with other stimuli regulate the expression of 479 of the 906 genes in the reconstructed metabolic network. This model is able not only to predict the outcomes of high-throughput growth phenotyping and gene expression experiments, but also to indicate knowledge gaps and identify previously unknown components and interactions in the regulatory and metabolic networks. We find that a systems biology approach that combines genome-scale experimentation and computation can systematically generate hypotheses on the basis of disparate data sources.",
author = "Covert, \{Markus W.\} and Knight, \{Eric M.\} and Reed, \{Jennifer L.\} and Herrgard, \{Markus J.\} and Palsson, \{Bernhard O.\}",
note = "Funding Information: Acknowledgements We would like to thank T. Hupp for his contribution of reagents and thought-provoking discussions, G. Lozano for p532/2/MDM22/2 MEFs, S. Benchimol for the Pirh2 antibody and cDNA, J. Chen for H1299 cells, B. Henzel for mass spectrometry support, C. Reed for the generation of COP1 monoclonal antibodies, M. Vasser and P. Ng for oligonucleotide synthesis and purification, A. Waugh for Bioinformatics support, Genentech Protein Engineering and core DNA sequencing facility for support services, and P. Polakis and members of the Dixit lab for advice and encouragement. I.W. is supported by a PSTP fellowship from the University of California, Davis. Funding Information: Acknowledgements We thank K. Stadsklev and A. Fleming for assistance with computation; Z. Zhang and A. Raghunathan for experimental assistance; the Perna and Blattner laboratories for access to the high-throughput phenotyping data in the ASAP database; and the NIH for funding and support. M.W.C. and B.O.P. designed the project and were involved in all phases of the study; E.M.K. carried out experiments; J.L.R. reconstructed the model, ran simulations and did the phenotyping analysis; M.J.H. did the statistical analysis of the gene expression data.",
year = "2004",
month = may,
day = "6",
doi = "10.1038/nature02456",
language = "English",
volume = "429",
pages = "92--96",
journal = "Nature",
issn = "0028-0836",
publisher = "Nature Research",
number = "6987",
}