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However, current systems classify all genes that belong to a specific EC family to all the pathways that contain the corresponding enzymatic reaction, and thus introduce ambiguity.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Here we describe an algorithm for assignment of genes to cellular pathways that addresses this problem by selectively assigning <jats:bold>specific<\/jats:bold> genes to pathways. Our algorithm uses the set of experimentally elucidated metabolic pathways from MetaCyc, together with statistical models of enzyme families and expression data to assign genes to enzyme families and pathways by optimizing correlated co-expression, while minimizing conflicts due to shared assignments among pathways. Our algorithm also identifies alternative (\"backup\") genes and addresses the multi-domain nature of proteins.<\/jats:p>\n                <jats:p>We apply our model to assign genes to pathways in the Yeast genome and compare the results for genes that were assigned experimentally. Our assignments are consistent with the experimentally verified assignments and reflect characteristic properties of cellular pathways.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>We present an algorithm for automatic assignment of genes to metabolic pathways. The algorithm utilizes expression data and reduces the ambiguity that characterizes assignments that are based only on EC numbers.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/1471-2105-6-217","type":"journal-article","created":{"date-parts":[[2005,8,31]],"date-time":"2005-08-31T18:13:33Z","timestamp":1125512013000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Automation of gene assignments to metabolic pathways using high-throughput expression data"],"prefix":"10.1186","volume":"6","author":[{"given":"Liviu","family":"Popescu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Golan","family":"Yona","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2005,8,31]]},"reference":[{"key":"542_CR1","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1093\/nar\/25.1.37","volume":"25","author":"E Selkov","year":"1997","unstructured":"Selkov E, Galimova M, Goryanin I, Gretchkin Y, Ivanova N, Komarov Y, Maltsev N, Mikhailova N, Nenashev V, Overbeek R, Panyushkina E, Pronevitch L, Selkov JE: The metabolic pathway collection: an update. 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