Machine Learning in Drug Development: Part Two, Volume 65 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this volume explore Transforming Modern Drug Discovery with Machine Learning - Applications in Ligand-based Drug Design, Optimizing Multi-Modal Drug Design Through Computational Pocket Mapping and Data Integration, Harnessing AI for Nucleic Acid Drug Discovery: Small Molecule Targeting DNA and RNA, AI-aided Drug Development for Protein Degraders: Design, Lead Identification, and Optimization, and more.
Additional section delve into Artificial Intelligence in the Development of Antiviral Drugs - Progress and Applications, Artificial Intelligence for Drug Target Identification, and Machine Learning in Proteomic Biomarker Discovery
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Table of Contents
1. Transforming Modern Drug Discovery with Machine Learning Applications in Ligand-based Drug Design2. Optimizing Multi-Modal Drug Design Through Computational Pocket Mapping and Data Integration
3. Harnessing AI for Nucleic Acid Drug Discovery: Small Molecule Targeting DNA and RNA
4. AI-aided Drug Development for Protein Degraders: Design, Lead Identification, and Optimization
5. Artificial Intelligence in the Development of Antiviral Drugs Progress and Applications
6. Artificial Intelligence for Drug Target Identification
7. Machine Learning in Proteomic Biomarker Discovery
