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Anomalies in network bridges involved in bile Acid metabolism predict outcomes of colorectal cancer patients.

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dc.contributor.authorLee, S-
dc.contributor.authorLee, K-
dc.contributor.authorYoon, S-
dc.contributor.authorLee, JW-
dc.contributor.authorLee, D-
dc.date.accessioned2015-12-09T01:50:07Z-
dc.date.available2015-12-09T01:50:07Z-
dc.date.issued2014-
dc.identifier.urihttp://repository.ajou.ac.kr/handle/201003/12223-
dc.description.abstractBiomarkers prognostic for colorectal cancer (CRC) would be highly desirable in clinical practice. Proteins that regulate bile acid (BA) homeostasis, by linking metabolic sensors and metabolic enzymes, also called bridge proteins, may be reliable prognostic biomarkers for CRC. Based on a devised metric, "bridgeness," we identified bridge proteins involved in the regulation of BA homeostasis and identified their prognostic potentials. The expression patterns of these bridge proteins could distinguish between normal and diseased tissues, suggesting that these proteins are associated with CRC pathogenesis. Using a supervised classification system, we found that these bridge proteins were reproducibly prognostic, with high prognostic ability compared to other known markers.-
dc.language.isoen-
dc.subject.MESHBile Acids and Salts-
dc.subject.MESHColorectal Neoplasms-
dc.subject.MESHHumans-
dc.subject.MESHPatient Outcome Assessment-
dc.subject.MESHPrognosis-
dc.subject.MESHProtein Interaction Mapping-
dc.subject.MESHProteomics-
dc.subject.MESHReproducibility of Results-
dc.subject.MESHTumor Markers, Biological-
dc.titleAnomalies in network bridges involved in bile Acid metabolism predict outcomes of colorectal cancer patients.-
dc.typeArticle-
dc.identifier.pmid25259881-
dc.identifier.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4178056/-
dc.contributor.affiliatedAuthor이, 기영-
dc.type.localJournal Papers-
dc.identifier.doi10.1371/journal.pone.0107925-
dc.citation.titlePloS one-
dc.citation.volume9-
dc.citation.number9-
dc.citation.date2014-
dc.citation.startPagee107925-
dc.citation.endPagee107925-
dc.identifier.bibliographicCitationPloS one, 9(9). : e107925-e107925, 2014-
dc.identifier.eissn1932-6203-
dc.relation.journalidJ019326203-
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Biomedical Informatics
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