Deep Learning For The Life Sciences
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Deep Learning For The Life Sciences
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Author : Bharath Ramsundar
language : en
Publisher:
Release Date : 2019
Deep Learning For The Life Sciences written by Bharath Ramsundar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.
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
Machine Learning In Biotechnology And Life Sciences
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Author : Saleh Alkhalifa
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-01-28
Machine Learning In Biotechnology And Life Sciences written by Saleh Alkhalifa and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-28 with Mathematics categories.
Explore all the tools and templates needed for data scientists to drive success in their biotechnology careers with this comprehensive guide Key FeaturesLearn the applications of machine learning in biotechnology and life science sectorsDiscover exciting real-world applications of deep learning and natural language processingUnderstand the general process of deploying models to cloud platforms such as AWS and GCPBook Description The booming fields of biotechnology and life sciences have seen drastic changes over the last few years. With competition growing in every corner, companies around the globe are looking to data-driven methods such as machine learning to optimize processes and reduce costs. This book helps lab scientists, engineers, and managers to develop a data scientist's mindset by taking a hands-on approach to learning about the applications of machine learning to increase productivity and efficiency in no time. You'll start with a crash course in Python, SQL, and data science to develop and tune sophisticated models from scratch to automate processes and make predictions in the biotechnology and life sciences domain. As you advance, the book covers a number of advanced techniques in machine learning, deep learning, and natural language processing using real-world data. By the end of this machine learning book, you'll be able to build and deploy your own machine learning models to automate processes and make predictions using AWS and GCP. What you will learnGet started with Python programming and Structured Query Language (SQL)Develop a machine learning predictive model from scratch using PythonFine-tune deep learning models to optimize their performance for various tasksFind out how to deploy, evaluate, and monitor a model in the cloudUnderstand how to apply advanced techniques to real-world dataDiscover how to use key deep learning methods such as LSTMs and transformersWho this book is for This book is for data scientists and scientific professionals looking to transcend to the biotechnology domain. Scientific professionals who are already established within the pharmaceutical and biotechnology sectors will find this book useful. A basic understanding of Python programming and beginner-level background in data science conjunction is needed to get the most out of this book.
Deep Learning For Life Sciences
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Author : Filippo Biscarini
language : en
Publisher: Springer Nature
Release Date : 2026-01-01
Deep Learning For Life Sciences written by Filippo Biscarini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Science categories.
Artificial intelligence is already ubiquitous in the life sciences, from cancer diagnosis to medical image analysis, from precision agriculture to wildlife monitoring. It is therefore essential for any scientist, especially life scientists, to have a basic understanding of deep learning, the statistical engine behind AI. This book explains the theory behind neural networks and their internal workings in clear terms and with numerous examples. The authors cover the building blocks of neural networks, the mathematical theory, different types of network architectures, the problem of overfitting, and the strategies to avoid it. The most common data types encountered in biological problems are discussed, with suggestions on how to apply deep learning to different cases. Success and failure stories are presented through interviews with leading experts in the field. The book is accompanied by several Python notebooks with practical examples and clearly commented code.
Deep Learning In Biology And Medicine
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Author : Davide Bacciu
language : en
Publisher: World Scientific
Release Date : 2022-01-17
Deep Learning In Biology And Medicine written by Davide Bacciu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-17 with Computers categories.
Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.
Machine Learning In Biological Sciences
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Author : Shyamasree Ghosh
language : en
Publisher: Springer Nature
Release Date : 2022-05-04
Machine Learning In Biological Sciences written by Shyamasree Ghosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-04 with Medical categories.
This book gives an overview of applications of Machine Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences. Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine. This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which forms a major domain of research in the field of biology. It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.
Next Gen Biology Ai S Transformative Impact On Life Sciences
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Author : Jasmine Jemimah Jeyanthi R
language : en
Publisher: OrangeBooks Publication
Release Date : 2025-03-19
Next Gen Biology Ai S Transformative Impact On Life Sciences written by Jasmine Jemimah Jeyanthi R and has been published by OrangeBooks Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-19 with Science categories.
The book "Next-Gen Biology: AI's Transformative impact on Life sciences" explores the integration of AI in biotechnology, healthcare, and agriculture. It delves into fundamental AI concepts, machine learning applications in clinical and genomic diagnostics, and AI-driven approaches for diagnosing genetic, psychiatric, and infectious diseases. The book also highlights AI's role in systems biology, pharmacogenomics, and disease management, including its impact on pandemic response. Additionally, it examines AI-powered advancements in agriculture, such as soil analysis, weather tracking, and satellite imaging. By bridging AI with biotechnology, the book provides a comprehensive understanding of its transformative potential in research, diagnostics, and sustainable development.
Marvels Of Artificial And Computational Intelligence In Life Sciences
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Author : Thirunavukkarasu Sivaraman
language : en
Publisher: Bentham Science Publishers
Release Date : 2023-09-20
Marvels Of Artificial And Computational Intelligence In Life Sciences written by Thirunavukkarasu Sivaraman and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-20 with Computers categories.
Marvels of Artificial and Computational Intelligence in Life Sciences is a primer for scholars and students who are interested in the applications of artificial intelligence (AI and computational intelligence (CI) in life sciences and other industries. The book consists of 16 chapters (9 of which focus on AI and 7 which showcase the benefits of CI approaches to solve specific problems). Chapters are edited by subject experts who describe the roles and applications of AI and CI in different parts of our lives in a concise and lucid manner. The book covers the following key themes: AI Revolution in Healthcare and Drug Discovery: AI's Impact on Biology and Energy Management AI and CI in Physical Sciences and Predictive Modeling Computational Biology The editors have compiled a good blend of topics in applied science and engineering to give readers a clear understanding of the multidisciplinary nature of the two facets of computing. Each chapter includes references for advanced readers.
Blockchain In Life Sciences
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Author : Wendy Charles
language : en
Publisher: Springer Nature
Release Date : 2022-08-30
Blockchain In Life Sciences written by Wendy Charles and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-30 with Computers categories.
This book highlights the latest advances on the implementation and adaptation of blockchain technologies in real-world scientific, biomedical, and data applications. It presents rapid advancements in life sciences research and development by applying the unique capabilities inherent in distributed ledger technologies. The book unveils the current uses of blockchain in drug discovery, drug and device tracking, real-world data collection, and increased patient engagement used to unlock opportunities to advance life sciences research. This paradigm shift is explored from the perspectives of pharmaceutical professionals, biotechnology start-ups, regulatory agencies, ethical review boards, and blockchain developers. This book enlightens readers about the opportunities to empower and enable data in life sciences.
The Role Of Artificial Intelligence In Advancing Applied Life Sciences
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Author : Emara, Tamer
language : en
Publisher: IGI Global
Release Date : 2025-04-29
The Role Of Artificial Intelligence In Advancing Applied Life Sciences written by Emara, Tamer and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Science categories.
The transformative role of artificial intelligence (AI) is revolutionizing the life sciences sector. AI is being used to accelerate drug discovery, personalize treatments, and improve patient outcomes. AI has demonstrated its potential in optimizing crop yields, enhancing food safety, and addressing global food security challenges. Additionally, AI has applications in climate modeling, species conservation, and pollution monitoring. Discussion of AI implementation in life sciences may stimulate further research and development in AI-driven life science solutions. The Role of Artificial Intelligence in Advancing Applied Life Sciences equips readers with a solid understanding of technology's potential to address complex life science problems. It also discusses the ethical implications and challenges associated with AI implementation in this field. Covering topics such as biomanufacturing, disease identification, and climate change patters, this book is an excellent resource for life scientists, computer scientists, healthcare practitioners, environmentalists, agriculturalists, professionals, researchers, scholars, academicians, and more.
Deep Learning For Life Sciences
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Author : Filippo Biscarini
language : en
Publisher: Springer
Release Date : 2026-01-13
Deep Learning For Life Sciences written by Filippo Biscarini and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-13 with Science categories.
Artificial intelligence is already ubiquitous in the life sciences, from cancer diagnosis to medical image analysis, from precision agriculture to wildlife monitoring. It is therefore essential for any scientist, especially life scientists, to have a basic understanding of deep learning, the statistical engine behind AI. This book explains the theory behind neural networks and their internal workings in clear terms and with numerous examples. The authors cover the building blocks of neural networks, the mathematical theory, different types of network architectures, the problem of overfitting, and the strategies to avoid it. The most common data types encountered in biological problems are discussed, with suggestions on how to apply deep learning to different cases. Success and failure stories are presented through interviews with leading experts in the field. The book is accompanied by several Python notebooks with practical examples and clearly commented code.