Open Access Databases and Datasets for Drug Discovery 1st Edition

Grab the edge in modern drug research with Open Access Databases and Datasets for Drug Discovery, 1st Edition by Antoine Daina, Michael Przewosny, and Vincent Zoete — a practical, up-to-date guide that puts the world’s richest public chemical and biological data at your fingertips.

Explore how freely available resources can accelerate target identification, virtual screening, lead optimization, and machine learning workflows. This book demystifies major open repositories, explains dataset curation and quality assessment, and offers clear strategies for integrating cheminformatics and bioinformatics data into reproducible pipelines. Ideal for medicinal chemists, computational biologists, data scientists, and biotech professionals, it balances technical depth with accessible guidance.

Learn to navigate and exploit databases for compound activity, protein structures, ADMET predictions, and bioassay results — with real-world examples that translate theory into actionable research steps. Whether you work in academic labs in Europe, industry teams in North America, or biotech hubs across Asia, the methods and best practices here are globally applicable and immediately useful.

Packed with expert insight from leaders in the field, this edition helps you reduce time-to-hit, improve screening efficiency, and build robust datasets for AI-driven discovery. Clear diagrams, practical tips, and workflow recommendations make it an essential reference for anyone leveraging public data to solve complex drug discovery problems.

Elevate your research capabilities today — add Open Access Databases and Datasets for Drug Discovery, 1st Edition to your library and start turning open data into real-world breakthroughs.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.