A Biologist’s Guide to Artificial Intelligence
A Biologist’s Guide to Artificial Intelligence

Author: Ambreen Hamadani

Publisher: Elsevier

Published: 2024-03-15

Total Pages: 370

ISBN-13: 0443240000

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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

Using Artificial Intelligence in Chemistry and Biology
Using Artificial Intelligence in Chemistry and Biology

Author: Hugh Cartwright

Publisher: CRC Press

Published: 2008-05-05

Total Pages: 358

ISBN-13: 0849384141

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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

A Guide to Applied Machine Learning for Biologists
A Guide to Applied Machine Learning for Biologists

Author: Mohammad "Sufian" Badar

Publisher: Springer Nature

Published: 2023-06-21

Total Pages: 273

ISBN-13: 3031222067

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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.

Introduction to Artificial Intelligence: Understanding the Basics: A Comprehensive Guide to Artificial Intelligence
Introduction to Artificial Intelligence: Understanding the Basics: A Comprehensive Guide to Artificial Intelligence

Author: Konstantin Titov

Publisher: Konstantin Titov

Published: 2024-01-06

Total Pages: 120

ISBN-13:

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Definition and History of AI: Explore the origins and evolution of AI, from its humble beginnings to its current transformative impact. Types of AI: Delve into the different types of AI, from Narrow AI and General AI to the intriguing realm of Superintelligent AI. Data's Crucial Role: Understand the importance of data in AI, its various types (Structured, Unstructured, Semi-Structured), and how it drives AI innovation. Fundamentals of Machine Learning: Uncover the core concepts of machine learning, from Supervised vs. Unsupervised Learning to Reinforcement Learning and Common Algorithms. Neural Networks and Deep Learning: Learn the basics of neural networks, explore the power of deep learning, and grasp the significance of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Natural Language Processing (NLP): Gain insights into how AI understands language, including Sentiment Analysis, Chatbots, and Translation. Computer Vision: Discover the wonders of image recognition and object detection, along with the intricacies of Facial Recognition Technology. Robotics and Autonomous Systems: Explore AI's role in robotics, from AI-driven robots to self-driving cars and drones. Ethical Considerations: Delve into the ethical aspects of AI, addressing bias, fairness, privacy, and security concerns. Real-World Applications: Witness AI's impact across industries such as healthcare, finance, and retail, and glimpse into the future of AI in various sectors. Emerging Trends: Stay ahead of the curve by exploring quantum computing's synergy with AI and the convergence of AI with the Internet of Things (IoT). Career Paths: Learn about the diverse roles in AI and the essential skills required, as well as the exciting future of work in the AI field. Whether you're a fan of AI, a student eager to learn, or a seasoned professional, "Introduction to Artificial Intelligence: Understanding the Basics" provides you with the essential knowledge to grasp, appreciate, and effectively navigate the AI revolution. Get ready for an exciting adventure into the fascinating world of artificial intelligence.

Python for Biologists
Python for Biologists

Author: Martin Jones

Publisher: Createspace Independent Publishing Platform

Published: 2013

Total Pages: 248

ISBN-13:

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Python for biologists is a complete programming course for beginners that will give you the skills you need to tackle common biological and bioinformatics problems.

Artificial Intelligence For Science: A Deep Learning Revolution
Artificial Intelligence For Science: A Deep Learning Revolution

Author: Alok Choudhary

Publisher: World Scientific

Published: 2023-03-21

Total Pages: 803

ISBN-13: 9811265682

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This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources — telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.

The Zoologist's Guide to the Galaxy
The Zoologist's Guide to the Galaxy

Author: Arik Kershenbaum

Publisher: Penguin UK

Published: 2020-09-24

Total Pages: 368

ISBN-13: 0241986850

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DISCOVER HOW LIFE REALLY WORKS - ON EARTH AND IN SPACE 'A wonderfully insightful sidelong look at Earthly biology' Richard Dawkins 'Crawls with curious facts' Sunday Times _________________________ We are unprepared for the greatest discovery of modern science. Scientists are confident that there is alien life across the universe yet we have not moved beyond our perception of 'aliens' as Hollywood stereotypes. The time has come to abandon our fixation on alien monsters and place our expectations on solid scientific footing. Using his own expert understanding of life on Earth and Darwin's theory of evolution - which applies throughout the universe - Cambridge zoologist Dr Arik Kershenbaum explains what alien life must be like. This is the story of how life really works, on Earth and in space. _________________________ 'An entertaining, eye-opening and, above all, a hopeful view of what - or who - might be out there in the cosmos' Philip Ball, author of Nature's Patterns 'A fascinating insight into the deepest of questions: what might an alien actually look like' Lewis Dartnell, author of Origins 'If you don't want to be surprised by extraterrestrial life, look no further than this lively overview of the laws of evolution that have produced life on earth' Frans de Waal, author of Mama's Last Hug

Artificial Intelligence and Molecular Biology
Artificial Intelligence and Molecular Biology

Author: Lawrence Hunter

Publisher:

Published: 1993

Total Pages: 484

ISBN-13:

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These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. The enormous amount of data generated by the Human Genome Project and other large-scale biological research has created a rich and challenging domain for research in artificial intelligence. These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book. Lawrence Hunter is Director of the Machine Learning Project at the National Library of Medicine, National Institutes of Health.

Artificial Intelligence and Computational Dynamics for Biomedical Research
Artificial Intelligence and Computational Dynamics for Biomedical Research

Author: Ankur Saxena

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2022-11-07

Total Pages: 298

ISBN-13: 3110762048

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This work presents the latest development in the field of computational intelligence to advance Big Data and Cloud Computing concerning applications in medical diagnosis. As forum for academia and professionals it covers state-of-the-art research challenges and issues in the digital information & knowledge management and the concerns along with the solutions adopted in these fields.