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QSAR and machine learning applied for the analysis of (fluoro)quinolone activity.

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Title: QSAR and machine learning applied for the analysis of (fluoro)quinolone activity.
Authors: Buglak AA; Department of Molecular Biophysics and Polymer Physics, St. Petersburg State University, St. Petersburg, Russia., Chebotaev PP; Department of Molecular Biophysics and Polymer Physics, St. Petersburg State University, St. Petersburg, Russia., Zherdev AV; A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, Russia., Hendrickson OD; A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, Russia.
Source: Expert opinion on drug discovery [Expert Opin Drug Discov] 2025 Dec; Vol. 20 (12), pp. 1525-1547. Date of Electronic Publication: 2025 Nov 06.
Publication Type: Journal Article; Review
Journal Info: Publisher: Taylor & Francis Country of Publication: England NLM ID: 101295755 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1746-045X (Electronic) Linking ISSN: 17460441 NLM ISO Abbreviation: Expert Opin Drug Discov Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: QSAR and machine learning applied for the analysis of (fluoro)quinolone activity.
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  Data: <searchLink fieldCode="AU" term="%22Buglak+AA%22">Buglak AA</searchLink>; Department of Molecular Biophysics and Polymer Physics, St. Petersburg State University, St. Petersburg, Russia.<br /><searchLink fieldCode="AU" term="%22Chebotaev+PP%22">Chebotaev PP</searchLink>; Department of Molecular Biophysics and Polymer Physics, St. Petersburg State University, St. Petersburg, Russia.<br /><searchLink fieldCode="AU" term="%22Zherdev+AV%22">Zherdev AV</searchLink>; A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, Russia.<br /><searchLink fieldCode="AU" term="%22Hendrickson+OD%22">Hendrickson OD</searchLink>; A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, Russia.
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  Data: <searchLink fieldCode="JN" term="%22101295755%22">Expert opinion on drug discovery</searchLink> [Expert Opin Drug Discov] 2025 Dec; Vol. 20 (12), pp. 1525-1547. <i>Date of Electronic Publication: </i>2025 Nov 06.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Taylor+%26+Francis%22">Taylor & Francis </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101295755 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1746-045X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2217460441%22">17460441 </searchLink><i>NLM ISO Abbreviation: </i>Expert Opin Drug Discov <i>Subsets: </i>MEDLINE
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        Value: 10.1080/17460441.2025.2584312
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      – Code: eng
        Text: English
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        StartPage: 1525
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      – TitleFull: QSAR and machine learning applied for the analysis of (fluoro)quinolone activity.
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              M: 12
              Text: 2025 Dec
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              Y: 2025
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