Deep Learning for the Life Sciences (Paperback)

Bharath Ramsundar , Peter Eastman , Patrick Walters , Vijay Pande

Deep Learning for the Life Sciences (Paperback)

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商品描述

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

商品描述(中文翻譯)

深度學習已經在許多領域取得了顯著的成果。現在，它正在科學界廣泛應用，尤其是在生命科學領域。這本實用書籍教導開發人員和科學家如何在基因組學、化學、生物物理學、顯微鏡學、醫學分析等領域中使用深度學習。

這本書適合已經具備實踐經驗的開發人員和科學家，他們準備將自己的技能應用於生物學、基因學和藥物發現等科學應用。書中介紹了幾種深度網絡基本原理。你將跟隨一個案例研究，解決設計新療法的問題，這個案例涉及物理學、化學、生物學和醫學，代表了科學面臨的最大挑戰之一。

- 學習在分子數據上進行機器學習的基礎知識
- 理解為什麼深度學習是遺傳學和基因組學的強大工具
- 應用深度學習來理解生物物理系統
- 簡要介紹使用DeepChem進行機器學習
- 使用深度學習分析顯微鏡圖像
- 使用深度學習技術分析醫學掃描
- 了解變分自編碼器和生成對抗網絡
- 解釋模型的運作方式和工作原理

作者簡介

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.

作者簡介(中文翻譯)

Bharath Ramsundar是Computable的聯合創始人兼首席技術官（CTO），Computable是一家致力於為人工智慧應用建立去中心化數據市場的區塊鏈公司。Bharath還是DeepChem.io的首席開發人員和創建者，DeepChem.io是一個基於Tensorflow的開源軟件包，旨在使深度學習在藥物發現中的應用民主化，他還是moleculenet.ai基準套件的共同創建者。

Bharath Ramsundar在加州大學伯克利分校獲得了電機與計算機科學（EECS）和數學的學士學位，並在數學畢業班中榮獲畢業生代表。他最近在斯坦福大學（除了論文）的計算機科學專業獲得了博士學位，並在Pande小組的支持下獲得了Hertz獎學金，這是科學領域中最具選擇性的研究生獎學金。

Peter Eastman在斯坦福大學生物工程系開發計算化學和生物學軟件。

Pat Walters是Relay Therapeutics的計算和信息組的負責人。他的團隊致力於推動藥物發現的計算方法的新應用。

Vijay Pande博士是Andreessen Horowitz的一位總合夥人，他負責該公司在生物學和計算機科學交叉領域的投資，包括計算、機器學習和人工智能在生物學和醫療保健領域的廣泛應用，以及新型轉化性科學進展的應用。他還是斯坦福大學生物工程的兼職教授，他在計算機科學和生物學交叉領域的研究中提供指導，開創了計算方法及其在醫學和生物學中的應用，並發表了200多篇論文，擁有兩項專利和兩種新型藥物治療方法。

作為生物學和計算機科學交叉領域的企業家，Vijay是Folding@Home分散計算項目的創始人，該項目用於疾病研究，將計算機科學技術（如分散系統、機器學習和異常計算機架構）應用於生物學和醫學領域的發展和應用，無論是基礎研究還是新療法的開發。在斯坦福大學期間，Vijay還共同創辦了Globavir Biosciences，將他在斯坦福大學和Folding@Home的研究成果轉化為一家成功的初創企業，發現了對抗登革熱和埃博拉的治療方法。在十幾歲時，他是視頻遊戲初創企業Naughty Dog Software的第一位員工，該公司開發了Crash Bandicoot遊戲。

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