A Biologist S Guide To Artificial Intelligence
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A Biologist S Guide To Artificial Intelligence
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Author : Ambreen Hamadani
language : en
Publisher: Elsevier
Release Date : 2024-03-15
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 2024-03-15 with Computers 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
A Biologist S Guide To Artificial Intelligence
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Author : Ambreen Hamadani
language : en
Publisher: Elsevier
Release Date : 2024-03
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 2024-03 with Computers 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.
A Guide To Applied Machine Learning For Biologists
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Author : Mohammad "Sufian" Badar
language : en
Publisher:
Release Date : 2023
A Guide To Applied Machine Learning For Biologists written by Mohammad "Sufian" Badar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.
Using Artificial Intelligence In Chemistry And Biology
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Author : Hugh Cartwright
language : en
Publisher: CRC Press
Release Date : 2008-05-05
Using Artificial Intelligence In Chemistry And Biology written by Hugh Cartwright and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-05 with Science categories.
Possessing great potential power for gathering and managing data in chemistry, biology, and other sciences, Artificial Intelligence (AI) methods are prompting increased exploration into the most effective areas for implementation. A comprehensive resource documenting the current state-of-the-science and future directions of the field is required to
Artificial Intelligence Methods And Tools For Systems Biology
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Author : W. Dubitzky
language : en
Publisher: Springer
Release Date : 2005-01-05
Artificial Intelligence Methods And Tools For Systems Biology written by W. Dubitzky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-05 with Science categories.
This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain. As design blueprint, the book is intended for scientists and other professionals tasked with developing and using AI technologies in the context of life sciences research. As a user guide, this volume addresses the requirements of researchers to gain a basic understanding of key AI methodologies for life sciences research. Its emphasis is not on an intricate mathematical treatment of the presented AI methodologies. Instead, it aims at providing the users with a clear understanding and practical know-how of the methods. As a research agenda, the book is intended for computer and life science students, teachers, researchers, and managers who want to understand the state of the art of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. Our aim was to maintain the readability and accessibility of a textbook throughout the chapters, rather than compiling a mere reference manual. The book is also intended as a communication platform seeking to bride the cultural and technological gap among key systems biology disciplines. To support this function, contributors have adopted a terminology and approach that appeal to audiences from different backgrounds.
A Guide To Applied Machine Learning For Biologists
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Author : Mohammad "Sufian" Badar
language : en
Publisher: Springer Nature
Release Date : 2023-06-21
A Guide To Applied Machine Learning For Biologists written by Mohammad "Sufian" Badar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-21 with Science categories.
This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.
Artificial Intelligence
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Author : Blay Whitby
language : en
Publisher: One World (UK)
Release Date : 2003
Artificial Intelligence written by Blay Whitby and has been published by One World (UK) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
This jargon-free guide introduces the futuristic world of Artificial Intelligence, the science of creating machines that can think for themselves.
A Computer Scientist S Guide To Cell Biology
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Author : William Cohen
language : en
Publisher: Springer
Release Date : 2024-08-17
A Computer Scientist S Guide To Cell Biology written by William Cohen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-17 with Science categories.
Unlike the structured world of computer science, biology is complex, evolving, and often lacks clean abstract models. This book aims to serve as a guide for computer scientists who need to understand cell biology, breaking the field into three parts: biological mechanics, experimental methods, and language/nomenclature. While biological mechanics, which investigates cellular-level details, is covered by many texts, this book also focuses on experimental methods – how biologists conduct experiments and gather data - and on helping the reader understand the language and terminology of biology, which is rich but challenging for non-biologists. A Computer Scientist's Guide to Cell Biology uses a metaphor of biology as a strange land with an unfamiliar language and customs. The goal of the book is to provide a high-level introduction to cell biology, simplifying concepts and relating them to familiar ideas from computer science, so that working computer scientists can more effectively understand read recent research papers and results. This Second Edition contains a number of updates, including discussions of CRISPR, advances in DNA Sequencing, and mRNA vaccines. It serves as an easy-to-read travel guide for computer scientists navigating the intricate and sometimes perplexing terrain of cell biology, offering insights into experimental methods and helping bridge the gap between the structured world of computer science and the complexities of biological systems.
Bioinformatics Second Edition
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Author : Pierre Baldi
language : en
Publisher: MIT Press
Release Date : 2001-07-20
Bioinformatics Second Edition written by Pierre Baldi and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-20 with Computers categories.
A guide to machine learning approaches and their application to the analysis of biological data. An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory, which is the situation in molecular biology. The goal in machine learning is to extract useful information from a body of data by building good probabilistic models—and to automate the process as much as possible. In this book Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed both at biologists and biochemists who need to understand new data-driven algorithms and at those with a primary background in physics, mathematics, statistics, or computer science who need to know more about applications in molecular biology. This new second edition contains expanded coverage of probabilistic graphical models and of the applications of neural networks, as well as a new chapter on microarrays and gene expression. The entire text has been extensively revised.
Artificial Neural Networks
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Author : David J. Livingstone
language : en
Publisher: Humana Press
Release Date : 2011-10-09
Artificial Neural Networks written by David J. Livingstone and has been published by Humana Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-09 with Computers categories.
In this book, international experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. Methods involving the mapping and interpretation of Infra Red spectra and modelling environmental toxicology are included. This book is an excellent guide to this exciting field.