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Random-forest model for drug-target interaction prediction via Kullback-Leibler divergence (vol 14, 67, 2022)

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dc.contributor.authorAhn, Sangjin-
dc.contributor.authorLee, Si Eun-
dc.contributor.authorKim, Mi-hyun-
dc.date.accessioned2022-11-13T02:40:03Z-
dc.date.available2022-11-13T02:40:03Z-
dc.date.created2022-11-13-
dc.date.issued2022-11-
dc.identifier.issn1758-2946-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/86093-
dc.description.abstractFollowing publication of the original article [1], the authors identified a spelling in the title and in the body of the text. Incorrect: Kullbeck. Correct: Kullback. The original article has been corrected. © The Author(s) 2022.-
dc.language영어-
dc.language.isoen-
dc.publisherBMC-
dc.relation.isPartOfJOURNAL OF CHEMINFORMATICS-
dc.titleRandom-forest model for drug-target interaction prediction via Kullback-Leibler divergence (vol 14, 67, 2022)-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000878145100001-
dc.identifier.doi10.1186/s13321-022-00653-0-
dc.identifier.bibliographicCitationJOURNAL OF CHEMINFORMATICS, v.14, no.1-
dc.description.isOpenAccessY-
dc.identifier.scopusid2-s2.0-85141083106-
dc.citation.titleJOURNAL OF CHEMINFORMATICS-
dc.citation.volume14-
dc.citation.number1-
dc.contributor.affiliatedAuthorAhn, Sangjin-
dc.contributor.affiliatedAuthorLee, Si Eun-
dc.contributor.affiliatedAuthorKim, Mi-hyun-
dc.type.docTypeCorrection-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryChemistry, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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