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To continue with this progress, it is essential to efficiently integrate experimental data into metabolic modeling.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We present here an <jats:italic>in-silico<\/jats:italic> framework to infer relevant metabolic pathways for a particular phenotype under study based on its gene\/protein expression data. This framework is based on the Carbon Flux Path (CFP) approach, a mixed-integer linear program that expands classical path finding techniques by considering additional biophysical constraints. In particular, the objective function of the CFP approach is amended to account for gene\/protein expression data and influence obtained paths. This approach is termed integrative Carbon Flux Path (iCFP). We show that gene\/protein expression data also influences the stoichiometric balancing of CFPs, which provides a more accurate picture of active metabolic pathways. This is illustrated in both a theoretical and real scenario. Finally, we apply this approach to find novel pathways relevant in the regulation of acetate overflow metabolism in <jats:italic>Escherichia coli<\/jats:italic>. As a result, several targets which could be relevant for better understanding of the phenomenon leading to impaired acetate overflow are proposed.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>A novel mathematical framework that determines functional pathways based on gene\/protein expression data is presented and validated. We show that our approach is able to provide new insights into complex biological scenarios such as acetate overflow in <jats:italic>Escherichia coli<\/jats:italic>.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1752-0509-7-134","type":"journal-article","created":{"date-parts":[[2013,12,8]],"date-time":"2013-12-08T02:01:04Z","timestamp":1386468064000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways"],"prefix":"10.1186","volume":"7","author":[{"given":"Jon","family":"Pey","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaspar","family":"Valgepea","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angel","family":"Rubio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John E","family":"Beasley","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco J","family":"Planes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2013,12,8]]},"reference":[{"key":"1251_CR1","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1126\/science.1188015","volume":"329","author":"MG Vander Heiden","year":"2010","unstructured":"Vander Heiden MG, Locasale JW, Swanson KD, Sharfi H, Heffron GJ, Amador-Noguez D, Christofk HR, Wagner G, Rabinowitz JD, Asara JM, Cantley LC: Evidence for an alternative glycolytic pathway in rapidly proliferating cells. 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