From annotated genomes to metabolic flux models and kinetic parameter fitting. Export

@article{Segre2003From, abstract = {Significant advances in system-level modeling of cellular behavior can be achieved based on constraints derived from genomic information and on optimality hypotheses. For steady-state models of metabolic networks, mass conservation and reaction stoichiometry impose linear constraints on metabolic fluxes. Different objectives, such as maximization of growth rate or minimization of flux distance from a reference state, can be tested in different organisms and conditions. In particular, we have suggested that the metabolic properties of mutant bacterial strains are best described by an algorithm that performs a minimization of metabolic adjustment (MOMA) upon gene deletion. The increasing availability of many annotated genomes paves the way for a systematic application of these flux balance methods to a large variety of organisms. However, such a high throughput goal crucially depends on our capacity to build metabolic flux models in a fully automated fashion. Here we describe a pipeline for generating models from annotated genomes and discuss the current obstacles to full automation. In addition, we propose a framework for the integration of flux modeling results and high throughput proteomic data, which can potentially help in the inference of whole-cell kinetic parameters.}, address = {Lipper Center for Computational Genetics, Harvard Medical School, Boston, Massachusetts, USA.}, author = {Segr\`{e}, D. and Zucker, J. and Katz, J. and Lin, X. and D'haeseleer, P. and Rindone, W. P. and Kharchenko, P. and Nguyen, D. H. and Wright, M. A. and Church, G. M.}, citeulike-article-id = {822475}, citeulike-linkout-0 = {http://dx.doi.org/10.1089/153623103322452413}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/14583118}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=14583118}, doi = {10.1089/153623103322452413}, issn = {1536-2310}, journal = {OMICS}, keywords = {biocyc, fba, kinetics, metabolic-reconstruction}, number = {3}, pages = {301--316}, posted-at = {2008-07-21 23:20:44}, priority = {2}, title = {From annotated genomes to metabolic flux models and kinetic parameter fitting.}, url = {http://dx.doi.org/10.1089/153623103322452413}, volume = {7}, year = {2003} }

TY - JOUR ID - Segre2003From L3 - citeulike-article-id:822475 N2 - Significant advances in system-level modeling of cellular behavior can be achieved based on constraints derived from genomic information and on optimality hypotheses. For steady-state models of metabolic networks, mass conservation and reaction stoichiometry impose linear constraints on metabolic fluxes. Different objectives, such as maximization of growth rate or minimization of flux distance from a reference state, can be tested in different organisms and conditions. In particular, we have suggested that the metabolic properties of mutant bacterial strains are best described by an algorithm that performs a minimization of metabolic adjustment (MOMA) upon gene deletion. The increasing availability of many annotated genomes paves the way for a systematic application of these flux balance methods to a large variety of organisms. However, such a high throughput goal crucially depends on our capacity to build metabolic flux models in a fully automated fashion. Here we describe a pipeline for generating models from annotated genomes and discuss the current obstacles to full automation. In addition, we propose a framework for the integration of flux modeling results and high throughput proteomic data, which can potentially help in the inference of whole-cell kinetic parameters. IS - 3 JF - OMICS SN - 1536-2310 AD - Lipper Center for Computational Genetics, Harvard Medical School, Boston, Massachusetts, USA. EP - 316 TI - From annotated genomes to metabolic flux models and kinetic parameter fitting. VL - 7 SP - 301 KW - biocyc KW - fba KW - kinetics KW - metabolic-reconstruction AU - Segrè, D AU - Zucker, J AU - Katz, J AU - Lin, X AU - D'haeseleer, P AU - Rindone, WP AU - Kharchenko, P AU - Nguyen, DH AU - Wright, MA AU - Church, GM PY - 2003/// UR - http://dx.doi.org/10.1089/153623103322452413 ER -