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Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More 1st Edition

4.2 out of 5 stars 48 ratings

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Editorial Reviews

About the Author

Bharath Ramsundar is the co-founder and CTO of Computable, a blockchain company working to build a decentralized data marketplace for AI applications. Bharath is also the lead developer and creator of DeepChem.io, an open source package founded on Tensorflow that aims to democratize the use of deep-learning in drug-discovery, and the co-creator of the moleculenet.ai benchmark suite.

Bharath Ramsundar received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He recently finished his PhD in computer science at Stanford University (all but dissertation) with the Pande group, supported by a Hertz Fellowship, the most selective graduate fellowship in the sciences.



Peter Eastman develops software for computational chemistry and biology in the Bioengineering Department at Stanford University.



Pat Walters heads the Computation & Informatics group at Relay Therapeutics. His group focuses on novel applications of computational methods that drive drug discovery.



Vijay Pande, PhD is a general partner at Andreessen Horowitz where he leads the firm’s investments in companies at the cross section of biology and computer science including areas such as the application of computation, Machine Learning, and Artificial Intelligence broadly into Biology and Healthcare as well as the application of novel transformative scientific advances. He is also an Adjunct Professor of Bioengineering at Stanford, where he advises research at the intersection of Computer Science and Biology, pioneering computational methods and their application to medicine and biology, resulting in over 200 publications, two patents and two novel drug treatments.

As an entrepreneur at the convergence of biology and computer science, Vijay is the founder of the Folding@Home Distributed Computing Project for disease research that pushes the boundaries of the development and application of computer science techniques (such as distributed systems, machine learning, and exotic computer architectures) into biology and medicine, in both fundamental research as well as the development of new therapeutics. Also during his time at Stanford, Vijay co-founded Globavir Biosciences, where he translated his research advances at Stanford and Folding@Home into a successful startup, discovering cures for Dengue Fever and Ebola. In his teens, he was the first employee at video game startup Naughty Dog Software, maker of Crash Bandicoot.


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Product details

  • Publisher ‏ : ‎ O'Reilly Media; 1st edition (April 28, 2019)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 236 pages
  • ISBN-10 ‏ : ‎ 1492039837
  • ISBN-13 ‏ : ‎ 978-1492039839
  • Item Weight ‏ : ‎ 12.8 ounces
  • Dimensions ‏ : ‎ 7 x 0.5 x 9.19 inches
  • Customer Reviews:
    4.2 out of 5 stars 48 ratings

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4.2 out of 5 stars
4.2 out of 5
48 global ratings

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4.0 out of 5 stars Loaded with practical examples, a great primer both for life sciences and deep learning
By Reasonable Reviewer on August 1, 2019
I received Deep Learning specifically to write a review. That said, I try to be honest and open in all my reviews.

(Please see the enclosed pictures.)

I loved the level of detail in the book. It showed the deep learning code as well as demonstrated where to find data for learning and training systems.

The book took just the right level of technical depth both to be credible as well as remain interesting and allow the reader to engage in learning.

You can see from the table of contents just how much information is packed into this small book.

My one caveat is that much of the book revolves around using the DeepChem program that is only available for Mac and Linux users.

Chapter two alone is worth four stars as it is a detailed, but approachable description of deep learning.

If you are a Mac or Linux user then the review jumps to five stars.

As a Windows user, you are going to struggle a bit and have to imagine what the code might have done had you run it.

All in all, read this as a primer on life sciences and how they relate to potential deep learning applications.

If you are a Mac or Linux user then go beyond the basics and learn how to do some basic deep learning programming.
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Top reviews from other countries

Mr. P. Bilokon
5.0 out of 5 stars An excellent overview of applications of deep learning in the life sciences
Reviewed in the United Kingdom 🇬🇧 on May 11, 2020
Cliente Amazon
5.0 out of 5 stars Fantasticlo
Reviewed in Spain 🇪🇸 on January 23, 2020