DC Field | Value | Language |
---|---|---|
dc.contributor.author | Moon, Kyungduk | - |
dc.contributor.author | Lee, Kangbok | - |
dc.contributor.author | Chopra, Sunil | - |
dc.contributor.author | Kwon, Steve | - |
dc.date.accessioned | 2021-12-02T08:35:33Z | - |
dc.date.available | 2021-12-02T08:35:33Z | - |
dc.date.created | 2021-11-30 | - |
dc.date.issued | 2022-07 | - |
dc.identifier.issn | 0377-2217 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/107715 | - |
dc.description.abstract | Boolean network is a modeling tool that describes a dynamic system with binary variables and their logical transition formulas. Recent studies in precision medicine use a Boolean network to discover critical genetic alterations that may lead to cancer or target genes for effective therapies to individuals. In this paper, we study a logical inference problem in a Boolean network to find all such critical genetic alterations in a minimal (parsimonious) way. We propose a bilevel integer programming model to find a single minimal genetic alteration. Using the bilevel integer programming model, we develop a branch and bound algorithm that effectively finds all of the minimal alterations. Through a computational study with eleven Boolean networks from the literature, we show that the proposed algorithm finds solutions much faster than the state-of-the-art algorithms in large data sets. © 2021 Elsevier B.V. | - |
dc.language | English | - |
dc.publisher | Elsevier BV | - |
dc.relation.isPartOf | European Journal of Operational Research | - |
dc.title | Bilevel integer programming on a Boolean network for discovering critical genetic alterations in cancer development and therapy | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.ejor.2021.10.019 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | European Journal of Operational Research, v.300, no.2, pp.743 - 754 | - |
dc.identifier.wosid | 000819872700025 | - |
dc.citation.endPage | 754 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 743 | - |
dc.citation.title | European Journal of Operational Research | - |
dc.citation.volume | 300 | - |
dc.contributor.affiliatedAuthor | Moon, Kyungduk | - |
dc.contributor.affiliatedAuthor | Lee, Kangbok | - |
dc.identifier.scopusid | 2-s2.0-85118725908 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | INTERVENTION STRATEGIES | - |
dc.subject.keywordPlus | REGULATORY NETWORKS | - |
dc.subject.keywordPlus | SIGNALING NETWORKS | - |
dc.subject.keywordPlus | INTERSECTION CUTS | - |
dc.subject.keywordPlus | LINEAR BILEVEL | - |
dc.subject.keywordPlus | ALGORITHM | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordAuthor | Bioinformatics | - |
dc.subject.keywordAuthor | Boolean network | - |
dc.subject.keywordAuthor | Bilevel programming | - |
dc.subject.keywordAuthor | Branch and bound algorithm | - |
dc.relation.journalWebOfScienceCategory | Management | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Business & Economics | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
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