Deep Learning for the Life Sciences ― Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
- ISBN13：9781492039839
- 出版社：Oreilly & Associates Inc
- 作者：Bharath Ramsundar; Karl Leswing; Peter Eastman; Vijay Pande
- 裝訂／頁數：平裝／400頁
- 規格：24.1cm*17.8cm*1.9cm (高/寬/厚)
- 出版日：2019/05/05
商品簡介
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 physics, chemistry, biology and medicine. Using TensorFlow and the DeepChem library, this book introduces deep network primitives including image convolutional networks, 1D convolutions for genomics, graph 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 scientific applications such as biology, genetics, and drug discovery, as well as scientists interested in adding deep learning to their core skills.
作者簡介
Bharath Ramsundar is the co-founder and CTO of Datamined, a blockchain company enabling the construction of large biological datasets. Datamined aims to generate the datasets needed to accelerate the ongoing boom of AI in biotech. 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.
Karl Leswing is the Machine Learning Technical Lead at Schrödinger. Karl applies DeepChem to the real world problems of 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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