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Machine learning-enhanced QSAR modeling for predicting drug efficacy against the RET V804M kinase domain mutation.

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Title: Machine learning-enhanced QSAR modeling for predicting drug efficacy against the RET V804M kinase domain mutation.
Authors: R B; Laboratory of Integrative Genomics, Department of Integrative Biology, School of BioSciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India., Nagabushanam DS; School of Computer Science, Engineering and Information Systems, Vellore Institute of Technology, Vellore, India., Thirunavukarasu R; School of Computer Science, Engineering and Information Systems, Vellore Institute of Technology, Vellore, India. ramkumar.thirunavukarasu@vit.ac.in., C GPD; Laboratory of Integrative Genomics, Department of Integrative Biology, School of BioSciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India. georgepriyadoss@vit.ac.in.
Source: Molecular diversity [Mol Divers] 2026 May 27. Date of Electronic Publication: 2026 May 27.
Publication Type: Journal Article
Journal Info: Publisher: ESCOM Science Publishers Country of Publication: Netherlands NLM ID: 9516534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-501X (Electronic) Linking ISSN: 13811991 NLM ISO Abbreviation: Mol Divers Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22R+B%22">R B</searchLink>; Laboratory of Integrative Genomics, Department of Integrative Biology, School of BioSciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India.<br /><searchLink fieldCode="AU" term="%22Nagabushanam+DS%22">Nagabushanam DS</searchLink>; School of Computer Science, Engineering and Information Systems, Vellore Institute of Technology, Vellore, India.<br /><searchLink fieldCode="AU" term="%22Thirunavukarasu+R%22">Thirunavukarasu R</searchLink>; School of Computer Science, Engineering and Information Systems, Vellore Institute of Technology, Vellore, India. ramkumar.thirunavukarasu@vit.ac.in.<br /><searchLink fieldCode="AU" term="%22C+GPD%22">C GPD</searchLink>; Laboratory of Integrative Genomics, Department of Integrative Biology, School of BioSciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India. georgepriyadoss@vit.ac.in.
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  Data: <searchLink fieldCode="JN" term="%229516534%22">Molecular diversity</searchLink> [Mol Divers] 2026 May 27. <i>Date of Electronic Publication: </i>2026 May 27.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22ESCOM+Science+Publishers%22">ESCOM Science Publishers </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>9516534 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1573-501X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2213811991%22">13811991 </searchLink><i>NLM ISO Abbreviation: </i>Mol Divers <i>Subsets: </i>MEDLINE
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        Value: 10.1007/s11030-026-11588-1
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      – Code: eng
        Text: English
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      – TitleFull: Machine learning-enhanced QSAR modeling for predicting drug efficacy against the RET V804M kinase domain mutation.
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            – D: 27
              M: 05
              Text: 2026 May 27
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              Y: 2026
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