Big Data Analytics in Chemoinformatics and Bioinformatics 1st Edition

Big Data Analytics in Chemoinformatics and Bioinformatics (1st Edition) by Subhash Basak and Marjan Vračko is an essential guide for scientists and data professionals navigating the intersection of chemistry, biology and large-scale data. This clear, contemporary volume captures cutting-edge approaches to processing, modeling, and interpreting complex chemical and biological datasets.

Discover practical strategies and real-world case studies that show how machine learning, statistical modeling, and data mining accelerate drug discovery, genomics research, and molecular design. Written with both researchers and industry practitioners in mind, the book translates advanced algorithms into actionable workflows—covering feature engineering, predictive modeling, high-throughput screening, and network analysis—so you can apply techniques immediately in the lab or on the cloud.

Why this book matters: it bridges theory and practice without sacrificing rigor. Whether you’re a chemoinformatician, bioinformatician, computational biologist, or data scientist in pharma, biotech, or academia, you’ll gain the skills to turn terabytes of experimental and omics data into reproducible insights. Global in scope and relevant to research hubs across North America, Europe, and Asia, the text addresses diverse datasets from cheminformatics repositories to next-generation sequencing.

Equip yourself with a resource that balances methodology, case examples, and problem-solving guidance. If you’re aiming to strengthen your analytics toolkit, streamline discovery pipelines, or lead data-driven projects, this authoritative 1st edition is the practical companion you need. Add it to your professional library and accelerate your journey from raw data to scientific impact.

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