Deep Learning for the Life Sciences
by Bharath Ramsundar
Bharath Ramsundar's practical guide to applying deep learning across genomics, drug discovery, microscopy, and molecular design for life sciences
"Deep learning has already achieved remarkable results in many fields. Now it's making waves throughout the sciences broadly and the life sciences in particular".
Editorial Summary
Bharath Ramsundar's "Deep Learning for the Life Sciences" is a practical guide that teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ramsundar, the creator of DeepChem.io—an open source TensorFlow-based package that democratizes deep learning in drug discovery—brings his Stanford PhD expertise to this comprehensive tutorial. The book follows a case study on designing new therapeutics that ties together physics, chemistry, biology, and medicine, representing one of science's greatest challenges. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. DeepChem has become a foundational tool cited thousands of times across academic and industrial drug discovery ecosystems, making this the standard computational reference for the field.
Perspective
"This book makes drug discovery feel like a software engineering problem — and once Ramsundar shows you the molecular prediction pipelines, you can't unsee how much of modern biology has become a machine learning problem in disguise. The distinctive contribution is DeepChem itself: the book is inseparable from the open-source library, making it simultaneously a tutorial and a gateway to production-grade tools actually used in pharmaceutical research. Life scientists with programming skills and ML engineers who want to work in drug discovery will find this the most direct path into the field."
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