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. |
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| 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 |
| ISSN: | 1573-501X |
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| DOI: | 10.1007/s11030-026-11588-1 |
