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Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms.

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第一作者： Wakeel,Ahmed

第一单位： Department of Mathematics, University of Sialkot, Sialkot, 51310, Pakistan. wakeelahmed784@gmail.com.;Department of Mathematics, COMSATS University, Islamabad Lahore Campus, Lahore, 51000, Pakistan. wakeelahmed784@gmail.com.

作者： Wakeel,Ahmed ^[1] ; Shahid,Zaman ^[2] ; Eizzah,Asif ^[3] ; Kashif,Ali ^[4] ; Emad E,Mahmoud ^[5] ; Mamo Abebe,Asheboss ^[6]

作者单位： Department of Mathematics, University of Sialkot, Sialkot, 51310, Pakistan. wakeelahmed784@gmail.com.;Department of Mathematics, COMSATS University, Islamabad Lahore Campus, Lahore, 51000, Pakistan. wakeelahmed784@gmail.com. ^[1] Department of Mathematics, University of Sialkot, Sialkot, 51310, Pakistan.;Department of Mathematical and Physical Sciences, University of Nizwa, Nizwa, Oman. ^[2] Department of Mathematics, University of Sialkot, Sialkot, 51310, Pakistan. ^[3] Department of Mathematics, COMSATS University, Islamabad Lahore Campus, Lahore, 51000, Pakistan. ^[4] Department of Mathematics and Statistics, Collage of Science, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia. ^[5] Department of Mathematics, Wollega University, 395, Nekemte, Ethiopia. ^[6]

关键词 Anti-HIV-1 drugs Machine learning algorithm Python algorithm QSPR analysis Topological indices

DOI 10.1186/s13065-024-01266-4

PMID 39267184

发布时间 2024-09-15

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2024年18卷1期

167页

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Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms.

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Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms.

BMC chemistry

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BMC chemistry

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