{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,23]],"date-time":"2025-02-23T05:14:16Z","timestamp":1740287656500,"version":"3.37.3"},"reference-count":50,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2287,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: An observed metabolic response is the result of the coordinated activation and interaction between multiple genetic pathways. However, the complex structure of metabolism has meant that a compete understanding of which pathways are required to produce an observed metabolic response is not fully understood. In this article, we propose an approach that can identify the genetic pathways which dictate the response of metabolic network to specific experimental conditions.<\/jats:p><jats:p>Results: Our approach is a combination of probabilistic models for pathway ranking, clustering and classification. First, we use a non-parametric pathway extraction method to identify the most highly correlated paths through the metabolic network. We then extract the defining structure within these top-ranked pathways using both Markov clustering and classification algorithms. Furthermore, we define detailed node and edge annotations, which enable us to track each pathway, not only with respect to its genetic dependencies, but also allow for an analysis of the interacting reactions, compounds and KEGG sub-networks. We show that our approach identifies biologically meaningful pathways within two microarray expression datasets using entire KEGG metabolic networks.<\/jats:p><jats:p>Availability and implementation: An R package containing a full implementation of our proposed method is currently available from http:\/\/www.bic.kyoto-u.ac.jp\/pathway\/timhancock<\/jats:p><jats:p>Contact: \u00a0timhancock@kuicr.kyoto-u.ac.jp<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq344","type":"journal-article","created":{"date-parts":[[2010,6,30]],"date-time":"2010-06-30T02:27:41Z","timestamp":1277864861000},"page":"2128-2135","source":"Crossref","is-referenced-by-count":14,"title":["Mining metabolic pathways through gene expression"],"prefix":"10.1093","volume":"26","author":[{"given":"Timothy","family":"Hancock","sequence":"first","affiliation":[{"name":"1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan and 2Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST)"},{"name":"1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan and 2Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST)"}]},{"given":"Ichigaku","family":"Takigawa","sequence":"additional","affiliation":[{"name":"1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan and 2Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST)"},{"name":"1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan and 2Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST)"}]},{"given":"Hiroshi","family":"Mamitsuka","sequence":"additional","affiliation":[{"name":"1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan and 2Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST)"},{"name":"1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan and 2Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST)"}]}],"member":"286","published-online":{"date-parts":[[2010,6,29]]},"reference":[{"key":"2023012508015526600_B1","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1104\/pp.106.090431","article-title":"The metabolic response of heterotrophic Arabidopsis cells to oxidative stress","volume":"143","author":"Baxter","year":"2007","journal-title":"Plant physiol."},{"key":"2023012508015526600_B2","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1091\/mbc.e09-07-0597","article-title":"Growth-limiting intracellular metabolites in yeast growing under diverse nutrient limitations","volume":"21","author":"Boer","year":"2010","journal-title":"Mol. 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