Artificial Intelligence And Biological Sciences
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Artificial Intelligence And Biological Sciences
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Author : P. V. Mohanan (Toxicologist)
language : en
Publisher:
Release Date : 2025
Artificial Intelligence And Biological Sciences written by P. V. Mohanan (Toxicologist) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Science categories.
"Artificial intelligence (AI) can be generally defined as the ability or capacity of machines that can simulate the intelligence capability of higher organisms and the term was first coined by John McCarthy in 1956. AI has confirmed their root in many branches of research especially in mathematics, physiology, computing, biology and psychology. Ideally, an AI system should response logically, self-aware and the ability to learn from experience and be discern and respond according to the external environments. With deep learning and machine learning algorithm-based intellect systems that can perform the activities requiring human intellect can be developed"--
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.
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.
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
Contemporary Studies In Biological Sciences I
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Author : Semra BENZER
language : en
Publisher: Akademisyen Kitabevi
Release Date : 2023-12-31
Contemporary Studies In Biological Sciences I written by Semra BENZER and has been published by Akademisyen Kitabevi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-31 with Nature categories.
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods
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Author : Lilhore, Umesh Kumar
language : en
Publisher: IGI Global
Release Date : 2024-03-22
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods written by Lilhore, Umesh Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-22 with Computers 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.
British Qualifications
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Author : Kogan Page
language : en
Publisher: Kogan Page Publishers
Release Date : 2004
British Qualifications written by Kogan Page and has been published by Kogan Page Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business & Economics categories.
In a single volume, the new edition of this guide gives comprehensive coverage of the developments within the fast-changing field of professional, academic and vocational qualifications. career fields, their professional and accrediting bodies, levels of membership and qualifications, and is a one-stop guide for careers advisors, students and parents. It should also enable human resource managers to verify the qualifications of potential employees.
Mass Spectrometry In The Biological Sciences A Tutorial
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Author : M.L Gross
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Mass Spectrometry In The Biological Sciences A Tutorial written by M.L Gross and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
The developments in mass spectrometry over the past fifteen years have been impressive in their implications in bioanalytical chemistry. The achievements begin with the inventions of Cf-252 Plasma Desorption Mass Spectrometry by Macfarlane and Fourier Transform Mass Spectrometry by Comisarow and Marshall in the mid 1970s. The former showed the feasibility of producing large gas-phase ions from large biomolecules whereas the latter enhanced the capabilities for ion trapping especially in analytical mass spectrometry. A major achievement was the development by Barber of Fast Atom Bombardment (FAB) mass spectrometry, an advance that heralded a new era in biological mass spectrometry. Contemporary and routine instruments such as magnetic sectors and quadrupoles were rapidly adapted to F AB, and nearly the entire universe of small molecules became amenable to study by mass spectrometry. The introduction of FAB also paved the way for improvement of instrument capability. For example, the upper mass limit of magnet sector mass spectrometers was increased by nearly an order of magnitude by the instrument manufacturers. Furthermore, the technique of tandem mass spectrometry (MS/MS) was given new meaning because important structural information for biomolecules could now be produced for ions introduced by FAB into the tandem instrument. The evolution of MS/MS continues today with the development of ion traps, time-of-flight, and sector instruments equipped with array detection.
Artificial Intelligence Ai In Cell And Genetic Engineering
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Author : Sudip Mandal
language : en
Publisher: Springer Nature
Release Date : 2025-06-24
Artificial Intelligence Ai In Cell And Genetic Engineering written by Sudip Mandal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Technology & Engineering categories.
This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering.
Computational Reconstruction Of Missing Data In Biological Research
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Author : Feng Bao
language : en
Publisher: Springer Nature
Release Date : 2021-08-06
Computational Reconstruction Of Missing Data In Biological Research written by Feng Bao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-06 with Computers categories.
The emerging biotechnologies have significantly advanced the study of biological mechanisms. However, biological data usually contain a great amount of missing information, e.g. missing features, missing labels or missing samples, which greatly limits the extensive usage of the data. In this book, we introduce different types of biological data missing scenarios and propose machine learning models to improve the data analysis, including deep recurrent neural network recovery for feature missings, robust information theoretic learning for label missings and structure-aware rebalancing for minor sample missings. Models in the book cover the fields of imbalance learning, deep learning, recurrent neural network and statistical inference, providing a wide range of references of the integration between artificial intelligence and biology. With simulated and biological datasets, we apply approaches to a variety of biological tasks, including single-cell characterization, genome-wide association studies, medical image segmentations, and quantify the performances in a number of successful metrics. The outline of this book is as follows. In Chapter 2, we introduce the statistical recovery of missing data features; in Chapter 3, we introduce the statistical recovery of missing labels; in Chapter 4, we introduce the statistical recovery of missing data sample information; finally, in Chapter 5, we summarize the full text and outlook future directions. This book can be used as references for researchers in computational biology, bioinformatics and biostatistics. Readers are expected to have basic knowledge of statistics and machine learning.