Identifying literature-based significant genes and discovering novel drug indications on PPI network
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박민석 | - |
dc.contributor.author | 장기업 | - |
dc.contributor.author | 이태건 | - |
dc.contributor.author | 윤영미 | - |
dc.date.available | 2020-02-27T22:41:16Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2017 | - |
dc.identifier.issn | 1598-849X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/7172 | - |
dc.description.abstract | New drug development is time-consuming and costly. Hence, it is necessary to repurpose old drugs for finding new indication. We suggest the way that repurposing old drug using massive literature data and biological network. We supposed a disease-drug relationship can be available if signal pathways of the relationship include significant genes identified in literature data. This research is composed of three steps-identifying significant gene using co-occurrence in literature; analyzing the shortest path on biological network; and scoring a relationship with comparison between the significant genes and the shortest paths. Based on literatures, we identify significant genes based on the co-occurrence frequency between a gene and disease. With the network that include weight as possibility of interaction between genes, we use shortest paths on the network as signal pathways. We perform comparing genes that identified as significant gene and included on signal pathways, calculating the scores and then identifying the candidate drugs. With this processes, we show the drugs having new possibility of drug repurposing and the use of our method as the new method of drug repurposing. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | 한국컴퓨터정보학회 | - |
dc.relation.isPartOf | 한국컴퓨터정보학회논문지 | - |
dc.title | Identifying literature-based significant genes and discovering novel drug indications on PPI network | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 2 | - |
dc.identifier.bibliographicCitation | 한국컴퓨터정보학회논문지, v.22, no.3, pp.131 - 138 | - |
dc.identifier.kciid | ART002210332 | - |
dc.citation.endPage | 138 | - |
dc.citation.startPage | 131 | - |
dc.citation.title | 한국컴퓨터정보학회논문지 | - |
dc.citation.volume | 22 | - |
dc.citation.number | 3 | - |
dc.contributor.affiliatedAuthor | 박민석 | - |
dc.contributor.affiliatedAuthor | 장기업 | - |
dc.contributor.affiliatedAuthor | 이태건 | - |
dc.contributor.affiliatedAuthor | 윤영미 | - |
dc.subject.keywordAuthor | Systems biology | - |
dc.subject.keywordAuthor | Network biology | - |
dc.subject.keywordAuthor | Text mining | - |
dc.subject.keywordAuthor | Drug repositioning | - |
dc.description.journalRegisteredClass | kci | - |
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