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In Silico Simulation of Signal Cascades in Biomedical Networks Based on the Production Rule System

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dc.contributor.author김상우-
dc.date.accessioned2018-07-20T08:15:39Z-
dc.date.available2018-07-20T08:15:39Z-
dc.date.issued2017-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/161021-
dc.description.abstractInferring novel findings from known biological knowledge is one of the ultimate goals in systems biology. However, the observation of system-level responses to a given perturbation has not been thoroughly explored due to the lack of proper large-scale inference models. We developed a novel expert system that can be applied to conventional biological networks based on the production rule system which works by transforming networks into a knowledgebase. Testing on large-scale multi-level biomedical networks confirmed the applicability of our system and revealed that hundreds of molecules are affected by the cascades of given signals, thereby activating or repressing key pathways in a cell.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherSpringer-
dc.relation.isPartOfLecture Notes in Computer Science-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.titleIn Silico Simulation of Signal Cascades in Biomedical Networks Based on the Production Rule System-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine-
dc.contributor.departmentDept. of Life Science-
dc.contributor.googleauthorSangwoo Kim-
dc.contributor.googleauthorHo Jung nam-
dc.identifier.doi10.1007/978-3-319-59575-7_34-
dc.contributor.localIdA00524-
dc.relation.journalcodeJ02160-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/978-3-319-59575-7_34-
dc.subject.keywordNetwork simulation-
dc.subject.keywordExpert system-
dc.subject.keywordProduction system-
dc.contributor.alternativeNameKim, Sang Woo-
dc.contributor.affiliatedAuthorKim, Sang Woo-
dc.citation.volume10330-
dc.citation.startPage356-
dc.citation.endPage361-
dc.identifier.bibliographicCitationLecture Notes in Computer Science, Vol.10330 : 356-361, 2017-
dc.identifier.rimsid60912-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > BioMedical Science Institute (의생명과학부) > 1. Journal Papers

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