Machine Learning In Biological Sciences
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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.
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.
Applications Of Machine Learning And Deep Learning On Biological Data
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Author :
language : en
Publisher:
Release Date : 2023-03
Applications Of Machine Learning And Deep Learning On Biological Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03 with categories.
"This book provides readers a comprehensive understanding of the application of machine Learning and deep Learning in proteomics, genomics, microarrays, text mining and related fields. The key objective is to provide machine learning applications to biological science problems, focusing on problems related to bioinformatics"--
Machine Learning And Iot
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Author : Shampa Sen
language : en
Publisher: CRC Press
Release Date : 2018-07-04
Machine Learning And Iot written by Shampa Sen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Computers categories.
This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine - from storing enormous amounts of biological data to solving complex biological problems and enhancing treatment of various grave diseases.
Computational And Analytic Methods In Biological Sciences
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Author : Akshara Makrariya
language : en
Publisher: CRC Press
Release Date : 2023-05-31
Computational And Analytic Methods In Biological Sciences written by Akshara Makrariya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Computers categories.
Despite major advances in healthcare over the past century, the successful treatment of cancer has remained a significant challenge, and cancers are the second leading cause of death worldwide behind cardiovascular disease. Early detection and survival are important issues to control cancer. The development of quantitative methods and computer technology has facilitated the formation of new models in medical and biological sciences. The application of mathematical modelling in solving many real-world problems in medicine and biology has yielded fruitful results. In spite of advancements in instrumentations technology and biomedical equipment, it is not always possible to perform experiments in medicine and biology for various reasons. Thus, mathematical modelling and simulation are viewed as viable alternatives in such situations, and are discussed in this book. The conventional diagnostic techniques of cancer are not always effective as they rely on the physical and morphological appearance of the tumour. Early stage prediction and diagnosis is very difficult with conventional techniques. It is well known that cancers are involved in genome level changes. As of now, the prognosis of various types of cancer depends upon findings related to the data generated through different experiments. Several machine learning techniques exist in analysing the data of expressed genes; however, the recent results related with deep learning algorithms are more accurate and accommodative, as they are effective in selecting and classifying informative genes. This book explores the probabilistic computational deep learning model for cancer classification and prediction.
Artificial Intelligence And Biological Sciences
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Author : P.V. Mohanan
language : en
Publisher: CRC Press
Release Date : 2025-06-17
Artificial Intelligence And Biological Sciences written by P.V. Mohanan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-17 with Computers categories.
Advancements of AI in medical and biological sciences have opened new ways for drug development. Novel therapeutic molecules and their target action can be easily predicted and can be modified. AI helps in disease detection and diagnosis faster. The breakthrough of AI is made especially in the area of personalized precision medicine, host-pathogen interaction and predictive epidemiology. These approaches could help in faster decision-making with minimal errors that can improve risk analysis, especially disease diagnosis and selecting treatment strategy. In agricultural practices, an exact combination of fertilizers, pesticides, herbicides, soil management, water requirement analysis, yield prediction and overall crop management can be modified by implementing AI interventions. AI could provide a better improvement in agriculture, medical research, pharmaceuticals and bio-based industries for a sustainable life. The key features of this book are: AI in medical Sciences, biotechnology and drug discovery; Application of AI in Digital Pathology, cytology and bioinformatics; Overview of AI, Machine Learning and Deep Learning; Impact of Artificial Intelligence in Society; Artificial Intelligence in Pharmacovigilance; and Ethics in Artificial Intelligence. The volume aims to comprehensively cover the application of AI in biological sciences. It is a collection of contributions from different authors who have several years of experience in their specific areas. The book will be useful for pharma companies, CROs, product developers, students, researchers, academicians, policymakers and practitioners.
A Biologist S Guide To Artificial Intelligence
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Author : Ambreen Hamadani
language : en
Publisher: Elsevier
Release Date : 2024-02-29
A Biologist S Guide To Artificial Intelligence written by Ambreen Hamadani and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-29 with Science categories.
A Biologist's Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist's perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future.This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. - Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learning - Equips with new data mining strategies an easy interface into the world of Artificial Intelligence - Enables researchers to enhance their own sphere of researching Artificial Intelligence
Signal Processing In Medicine And Biology
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Author : Ammar Ahmed
language : en
Publisher: Springer Nature
Release Date : 2025-09-19
Signal Processing In Medicine And Biology written by Ammar Ahmed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-19 with Technology & Engineering categories.
Signal Processing in Medicine and Biology: Applications of Deep Learning to the Health Sciences presents expanded versions of selected papers from the 2023 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB) at Temple University. The symposium presents multidisciplinary research across a wide range of topics in the life sciences. The Neural Engineering Data Consortium hosts the symposium to promote machine learning and big data applications in bioengineering. Topics covered include: !-- [if !supportLists]--· !--[endif]--Signal and image analysis (e.g., EEG, ECG, MRI); !-- [if !supportLists]--· !--[endif]--Machine learning, data mining, and classification; !-- [if !supportLists]--· !--[endif]--Big data resources and applications; !-- [if !supportLists]--· !--[endif]--Applications of quantum computing; !-- [if !supportLists]--· !--[endif]--Digital pathology; !-- [if !supportLists]--· !--[endif]--Computational biology; !-- [if !supportLists]--· !--[endif]--Genomics, genetics, proteomics. Applications of particular interest at the 2023 symposium included digital pathology, computational biology, genomics, genetics, and proteomics. The book features tutorials and examples of successful applications that will appeal to many professionals and researchers in signal processing, medicine, and biology. For students and professionals new to the field, the book offers an easy-to-understand introduction to various bioengineering topics. For professionals active in the field, it provides essential algorithmic details on valuable benchmarks for the technology.
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods
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Author : Vishal Dutt
language : en
Publisher:
Release Date : 2024
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods written by Vishal Dutt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics . This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences. Designed for academic scholars and practitioners, as well as upper-level undergraduates and graduates seeking to expand their knowledge, this book is a must-read for anyone passionate about the intersection of data science and human biology. Healthcare professionals, biotechnologists, and academics alike will find this resource invaluable for advancing their understanding and capabilities in the dynamic field of bioinformatics.
Deep Learning For The Life Sciences
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Author : Bharath Ramsundar
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-04-10
Deep Learning For The Life Sciences written by Bharath Ramsundar and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-10 with Science 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