{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T20:04:35Z","timestamp":1780344275694,"version":"3.54.1"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T00:00:00Z","timestamp":1562544000000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Academy of Finland Center of Excellence in Systems Immunology and Physiology, the Academy of Finland","award":["299915"],"award-info":[{"award-number":["299915"]}]},{"name":"Academy of Finland Center of Excellence in Systems Immunology and Physiology, the Academy of Finland","award":["313271"],"award-info":[{"award-number":["313271"]}]},{"name":"Innovation Tekes","award":["40128\/14"],"award-info":[{"award-number":["40128\/14"]}]},{"DOI":"10.13039\/501100003125","name":"Finnish Cultural Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003125","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Metabolic flux balance analysis (FBA) is a standard tool in analyzing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometry. Flux analysis methods commonly place model assumptions on fluxes due to the convenience of formulating the problem as a linear programing model, while many methods do not consider the inherent uncertainty in flux estimates.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We introduce a novel paradigm of Bayesian metabolic flux analysis that models the reactions of the whole genome-scale cellular system in probabilistic terms, and can infer the full flux vector distribution of genome-scale metabolic systems based on exchange and intracellular (e.g. 13C) flux measurements, steady-state assumptions, and objective function assumptions. The Bayesian model couples all fluxes jointly together in a simple truncated multivariate posterior distribution, which reveals informative flux couplings. Our model is a plug-in replacement to conventional metabolic balance methods, such as FBA. Our experiments indicate that we can characterize the genome-scale flux covariances, reveal flux couplings, and determine more intracellular unobserved fluxes in Clostridium acetobutylicum from 13C data than flux variability analysis.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The COBRA compatible software is available at github.com\/markusheinonen\/bamfa.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz315","type":"journal-article","created":{"date-parts":[[2019,5,9]],"date-time":"2019-05-09T19:21:53Z","timestamp":1557429713000},"page":"i548-i557","source":"Crossref","is-referenced-by-count":23,"title":["Bayesian metabolic flux analysis reveals intracellular flux couplings"],"prefix":"10.1093","volume":"35","author":[{"given":"Markus","family":"Heinonen","sequence":"first","affiliation":[{"name":"Department of Computer Science, Aalto University, Espoo, Finland"},{"name":"Helsinki Institute for Information Technology, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Osmala","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Aalto University, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henrik","family":"Mannerstr\u00f6m","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Aalto University, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janne","family":"Wallenius","sequence":"additional","affiliation":[{"name":"Institute for Molecular Medicine Finland, Helsinki, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Kaski","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Aalto University, Espoo, Finland"},{"name":"Helsinki Institute for Information Technology, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juho","family":"Rousu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Aalto University, Espoo, Finland"},{"name":"Helsinki Institute for Information Technology, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harri","family":"L\u00e4hdesm\u00e4ki","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Aalto University, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2019,7,5]]},"reference":[{"key":"2023062712385695900_btz315-B1","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1038\/nature02289","article-title":"Global organization of metabolic fluxes in the bacterium Escherichia coli","volume":"427","author":"Almaas","year":"2004","journal-title":"Nature"},{"key":"2023062712385695900_btz315-B2","author":"Altmann","year":"2014"},{"key":"2023062712385695900_btz315-B3","doi-asserted-by":"crossref","first-page":"727.","DOI":"10.1038\/nprot.2007.99","article-title":"Quantitative prediction of cellular metabolism with constraint-based models: the cobra toolbox","volume":"2","author":"Becker","year":"2007","journal-title":"Nat. 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