{"product_id":"deep-learning-for-the-life-sciences-applying-deep-learning-to-genomics-microscopy-drug-discovery-and-more-paperback","title":"Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eBharath Ramsundar\u003c\/b\u003e (Author), \u003cb\u003ePeter Eastman\u003c\/b\u003e (Author), \u003cb\u003ePatrick Walters\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eDeep learning has already achieved remarkable results in many fields. Now itâ 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. \u003c\/p\u003e\u003cp\u003e 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. Youâ ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicineâ an example that represents one of scienceâ s greatest challenges. \u003c\/p\u003e\u003cul\u003e \u003cli\u003eLearn the basics of performing machine learning on molecular data \u003c\/li\u003e\n\u003cli\u003eUnderstand why deep learning is a powerful tool for genetics and genomics \u003c\/li\u003e\n\u003cli\u003eApply deep learning to understand biophysical systems \u003c\/li\u003e\n\u003cli\u003eGet a brief introduction to machine learning with DeepChem \u003c\/li\u003e\n\u003cli\u003eUse deep learning to analyze microscopic images \u003c\/li\u003e\n\u003cli\u003eAnalyze medical scans using deep learning techniques \u003c\/li\u003e\n\u003cli\u003eLearn about variational autoencoders and generative adversarial networks \u003c\/li\u003e\n\u003cli\u003eInterpret what your model is doing and how itâ s working \u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eBharath 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.\u003c\/p\u003e\u003cp\u003eBharath 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.\u003c\/p\u003e\u003cp\u003ePeter Eastman develops software for computational chemistry and biology in the Bioengineering Department at Stanford University.\u003c\/p\u003e\u003cp\u003ePat Walters heads the Computation \u0026amp; Informatics group at Relay Therapeutics. His group focuses on novel applications of computational methods that drive drug discovery.\u003c\/p\u003e\u003cp\u003eVijay 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.\u003c\/p\u003e\u003cp\u003eAs 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.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 233\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.4 x 9.1 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e May 14, 2019\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52492500500787,"sku":"9781492039839","price":96.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/R1ovZ2JsNnBrcW51ZGw3MWFQRS9DUT09.webp?v=1759935547","url":"https:\/\/www.vysn.com\/en-ca\/products\/deep-learning-for-the-life-sciences-applying-deep-learning-to-genomics-microscopy-drug-discovery-and-more-paperback","provider":"VYSN","version":"1.0","type":"link"}