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Brown, Benjamin P. [Verfasser:in]; Vu, Oanh [Verfasser:in]; Geanes, Alexander R. [Verfasser:in]; Kothiwale, Sandeepkumar [Verfasser:in]; Butkiewicz, Mariusz [Verfasser:in]; Lowe Jr., Edward W. [Verfasser:in]; Mueller, Ralf [Verfasser:in]; Pape, Richard [Verfasser:in]; Mendenhall, Jeffrey [Verfasser:in]; Meiler, Jens [Verfasser:in]

Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery

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  • Medientyp: E-Artikel
  • Titel: Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery
  • Beteiligte: Brown, Benjamin P. [Verfasser:in]; Vu, Oanh [Verfasser:in]; Geanes, Alexander R. [Verfasser:in]; Kothiwale, Sandeepkumar [Verfasser:in]; Butkiewicz, Mariusz [Verfasser:in]; Lowe Jr., Edward W. [Verfasser:in]; Mueller, Ralf [Verfasser:in]; Pape, Richard [Verfasser:in]; Mendenhall, Jeffrey [Verfasser:in]; Meiler, Jens [Verfasser:in]
  • Erschienen: Lausanne: Frontiers Research Foundation, [2023]
  • Erschienen in: Frontiers in pharmacology ; 13, (2022)
  • Sprache: Englisch
  • Schlagwörter: drug discovery ; BCL ; biochemical library ; open-source ; QSAR ; drug design ; cheminformatics ; deep neural network
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: The BioChemical Library (BCL) cheminformatics toolkit is an application-based academicopen-source software package designed to integrate traditional small moleculecheminformatics tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide adetailed introduction to core BCL cheminformatics functionality, showing how traditionaltasks (e.g., computing chemical properties, estimating druglikeness) can be readilycombined with machine learning. In addition, we have included multiple examplescovering areas of advanced use, such as reaction-based library design. We anticipatethat this manuscript will be a valuable resource for researchers in computer-aided drugdiscovery looking to integrate modular cheminformatics and machine learning tools intotheir pipelines.
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Namensnennung (CC BY)