Deep Learning for the Life Sciences

Book Description

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

With much success already attributed to deep learning, this discipline has started making waves throughout science broadly and the life sciences in particular. With this practical book, developers and scientists will learn how deep learning is used for genomics, chemistry, biophysics, microscopy, medical analysis, drug discovery, and other fields.

As a running case study, the authors focus on the problem of designing new therapeutics, one of science’s greatest challenges because this practice ties together , chemistry, and medicine. Using TensorFlow and the DeepChem library, this book introduces deep network primitives including image convolutional networks, 1D convolutions for genomics, convolutions for molecular graphs, atomic convolutions for molecular structures, and molecular autoencoders.

Deep Learning for the Life Sciences is ideal for practicing developers interested in applying their skills to such as biology, genetics, and drug discovery, as well as scientists interested in adding deep learning to their core skills.

Table of Contents

Chapter 1. with DeepChem
Chapter 2. Machine Learning For Molecules
Chapter 3. Interpretation of Deep
Chapter 4. A Virtual Screening Workflow Example

Book Details

File HostFree Download LinkFormatSize (MB)Upload Date
UsersCloud Click to downloadPDF (Early Release)4.111/28/2018
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