Deep learning for the life sciences : applying deep learning to genomics, microscopy, drug discovery and more

Responsibility: Bahrath Ramsundar, Peter Eastman, Patrick Walters, and Vijay Pande.
Edition: First edition.
Publication: Sebastopol, CA : O'Reilly Media, [2019]
Copyright notice: ©2019
Physical description: x, 222 pages : illustrations ; 24 cm

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Call number	Note	Status
QH307.2 .R36 2019		Unknown

Author/Creator: Ramsundar, Bharath, author.
Contributor: Eastman, Peter, author.; Walters, Patrick, author.; Pande, Vijay author.

Bibliography: Includes bibliographical references and index.
Publisher's summary: 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. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. 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. You'll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine-an example that represents one of science's greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it's working.
(source: Nielsen Book Data)

Subjects: Life sciences > Data processing.; Machine learning.; Artificial intelligence.

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