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Using Artificial Intelligence In Chemistry And Biology
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Book Synopsis Using Artificial Intelligence in Chemistry and Biology by : Hugh Cartwright
Download or read book Using Artificial Intelligence in Chemistry and Biology written by Hugh Cartwright and published by CRC Press. This book was released on 2008-05-05 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Using Artificial Intelligence in Chemistry and Biology by : Hugh Cartwright
Download or read book Using Artificial Intelligence in Chemistry and Biology written by Hugh Cartwright and published by CRC Press. This book was released on 2019-08-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 furnish the working experimental scientist and newcomer alike with the background necessary to utilize these methods. In response to the growing interest in the potential scientific applications of AI, Using Artificial Intelligence in Chemistry and Biology explains in a lucid, straightforward manner how these methods are used by scientists and what can be accomplished with them. Designed for those with no prior knowledge of AI, computer science, or programming, this book efficiently and quickly takes you to the point at which meaningful scientific applications can be investigated. The approach throughout is practical and direct, employing figures and illustrations to add clarity and humor to the topics at hand. Unique in scope, addressing the needs of scientists across a range of disciplines, this book provides both a broad overview and a detailed introduction to each of the techniques discussed. Chapters include an introduction to artificial intelligence, artificial neural networks, self-organizing maps, growing cell structures, evolutionary algorithms, cellular automata, expert systems, fuzzy logic, learning classifier systems, and evolvable developmental systems. The book also comes with a CD containing a complete version of the EJS software with which most of the calculations were accomplished. Encouraging a broader application of AI methods, this seminal work gives software designers a clearer picture of how scientists use AI and how to address those needs, and provides chemists, biologists, physicists, and others with the tools to increase the speed and efficiency of their work.
Book Synopsis Machine Learning in Chemistry by : Hugh M. Cartwright
Download or read book Machine Learning in Chemistry written by Hugh M. Cartwright and published by Royal Society of Chemistry. This book was released on 2020-07-15 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.
Book Synopsis Artificial Intelligence in Drug Discovery by : Nathan Brown
Download or read book Artificial Intelligence in Drug Discovery written by Nathan Brown and published by Royal Society of Chemistry. This book was released on 2020-11-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.
Book Synopsis Machine Learning in Chemistry by : Jon Paul Janet
Download or read book Machine Learning in Chemistry written by Jon Paul Janet and published by American Chemical Society. This book was released on 2020-05-28 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important
Book Synopsis Artificial Intelligence in Bioinformatics and Chemoinformatics by : Yashwant Pathak
Download or read book Artificial Intelligence in Bioinformatics and Chemoinformatics written by Yashwant Pathak and published by CRC Press. This book was released on 2023-10-11 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors aim to shed light on the practicality of using machine learning in finding complex chemoinformatics and bioinformatics applications as well as identifiying AI in biological and chemical data points. The chapters are designed in such a way that they highlight the important role of AI in chemistry and bioinformatics particularly for the classification of diseases, selection of features and compounds, dimensionality reduction and more. In addition, they assist in the organization and optimal use of data points generated from experiments performed using AI techniques. This volume discusses the development of automated tools and techniques to aid in research plans. Features Covers AI applications in bioinformatics and chemoinformatics Demystifies the involvement of AI in generating biological and chemical data Provides an Introduction to basic and advanced chemoinformatics computational tools Presents a chemical biology based toolset for artificial intelligence usage in drug design Discusses computational methods in cancer, genome mapping, and stem cell research
Book Synopsis Artificial Intelligence in Chemistry by : José S. Torrecilla
Download or read book Artificial Intelligence in Chemistry written by José S. Torrecilla and published by Frontiers Media SA. This book was released on 2020-07-17 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applications of Artificial Intelligence in Chemistry by : Hugh M. Cartwright
Download or read book Applications of Artificial Intelligence in Chemistry written by Hugh M. Cartwright and published by Oxford University Press on Demand. This book was released on 1993 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is clear that the techniques of artificial intelligence are useful for more than just the development of thinking machines; they constitute powerful problem-solving tools in their own right and expand the range of problems in science that can be tackled. AI methods can now be used on a routine basis by scientists in academic research as well as the commercial world, it is therefore vital that science students are exposed to, and understand these techniques. This is the first book topresent an introduction to AI methods for science undergraduates. The examples are drawn mainly from chemistry but the book is suited to a general scientific audience wanting to know more about how computers can help to understand and interpret science.
Book Synopsis Artificial Intelligence in Drug Design by : Alexander Heifetz
Download or read book Artificial Intelligence in Drug Design written by Alexander Heifetz and published by Humana. This book was released on 2022-11-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.
Book Synopsis Advances in Artificial Intelligence, Computation, and Data Science by : Tuan D. Pham
Download or read book Advances in Artificial Intelligence, Computation, and Data Science written by Tuan D. Pham and published by Springer Nature. This book was released on 2021-07-12 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has become pervasive in most areas of research and applications. While computation can significantly reduce mental efforts for complex problem solving, effective computer algorithms allow continuous improvement of AI tools to handle complexity—in both time and memory requirements—for machine learning in large datasets. Meanwhile, data science is an evolving scientific discipline that strives to overcome the hindrance of traditional skills that are too limited to enable scientific discovery when leveraging research outcomes. Solutions to many problems in medicine and life science, which cannot be answered by these conventional approaches, are urgently needed for society. This edited book attempts to report recent advances in the complementary domains of AI, computation, and data science with applications in medicine and life science. The benefits to the reader are manifold as researchers from similar or different fields can be aware of advanced developments and novel applications that can be useful for either immediate implementations or future scientific pursuit. Features: Considers recent advances in AI, computation, and data science for solving complex problems in medicine, physiology, biology, chemistry, and biochemistry Provides recent developments in three evolving key areas and their complementary combinations: AI, computation, and data science Reports on applications in medicine and physiology, including cancer, neuroscience, and digital pathology Examines applications in life science, including systems biology, biochemistry, and even food technology This unique book, representing research from a team of international contributors, has not only real utility in academia for those in the medical and life sciences communities, but also a much wider readership from industry, science, and other areas of technology and education.
Book Synopsis Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering by : Nenad Filipović
Download or read book Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering written by Nenad Filipović and published by Springer Nature. This book was released on with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Artificial Intelligence: Medicine, Biology, Chemistry, Financial, Games, Engineering by : Nenad Filipovic
Download or read book Applied Artificial Intelligence: Medicine, Biology, Chemistry, Financial, Games, Engineering written by Nenad Filipovic and published by Springer Nature. This book was released on 2023-04-04 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is covering knowledge and results in theory, methodology, and applications of artificial intelligence and machine learning in academia and industry. Nowadays, artificial intelligence has been used in every company where intelligence elements are embedded inside sensors, devices, machines, computers and networks. The chapters in this book integrated approach toward global exchange of information on technological advances, scientific innovations, and the effectiveness of various regulatory programs toward AI application in medicine, biology, chemistry, financial, games, law, and engineering. Readers can find AI application in industrial workplace safety, manufacturing systems, medical imaging, biomedical engineering application, different computational paradigm, COVID-19, liver tracking, drug delivery system, and cost-effectiveness analysis. Real examples from academia and industry give beyond state of the art for application of AI and ML in different areas. These chapters are extended papers from the First Serbian International Conference on Applied Artificial Intelligence (SICAAI), which was held in Kragujevac, Serbia, on May 19–20, 2022.
Book Synopsis Artificial Intelligence in Chemical Engineering by : Thomas E. Quantrille
Download or read book Artificial Intelligence in Chemical Engineering written by Thomas E. Quantrille and published by Elsevier. This book was released on 2012-12-02 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is the part of computer science concerned with designing intelligent computer systems (systems that exhibit characteristics we associate with intelligence in human behavior). This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of AI into its applications in chemical engineering. After reading this book, a chemical engineer will have a firm grounding in AI, know what chemical engineering applications of AI exist today, and understand the current challenges facing AI in engineering. Allows the reader to learn AI quickly using inexpensive personal computers Contains a large number of illustrative examples, simple exercises, and complex practice problems and solutions Includes a computer diskette for an illustrated case study Demonstrates an expert system for separation synthesis (EXSEP) Presents a detailed review of published literature on expert systems and neural networks in chemical engineering
Book Synopsis The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry by : Stephanie K. Ashenden
Download or read book The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry written by Stephanie K. Ashenden and published by Academic Press. This book was released on 2021-04-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide
Book Synopsis Deep Learning In Biology And Medicine by : Davide Bacciu
Download or read book Deep Learning In Biology And Medicine written by Davide Bacciu and published by World Scientific. This book was released on 2022-01-17 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Chemical Biology by : Marco F. Schmidt
Download or read book Chemical Biology written by Marco F. Schmidt and published by Springer Nature. This book was released on 2022-01-31 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this textbook is on application, rather than pure knowledge transfer of the results of all chemical biological work (which would also be beyond the scope of a book). It gives the reader, through the specific selection of chemical biological techniques and concepts, the necessary tools to be able to develop new ways of thinking and thus new therapeutic options in the complex field of chemical biology and drug development. The stated aim of this book is to provide concrete solutions and inspiration to students, (post)graduate students, and experienced scientists at universities as well as in industry in their problems. After an introduction to the problems addressed by chemical biology in drug discovery, the three levels of molecular biology dogma: DNA, RNA and proteins and their role as drug targets serve as the common thread of this book. This book is a translation of the original German 1st edition Chemische Biologie by Marco F. Schmidt, published by Springer-Verlag GmbH Germany, part of Springer Nature in 2020. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors.
Book Synopsis Machine Learning and Artificial Intelligence in Chemical and Biological Sensing by : Jeong-Yeol Yoon
Download or read book Machine Learning and Artificial Intelligence in Chemical and Biological Sensing written by Jeong-Yeol Yoon and published by Elsevier. This book was released on 2024-07-22 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) has recently become popular in chemical and biological sensing applications. ML is a subset of artificial intelligence (AI) and other AI techniques have been used in various chemical and biological sensing. Machine Learning and Artificial Intelligence in Chemical and Biological Sensing covers the theoretical background and practical applications of various ML/AI methods toward chemical and biological sensing. No comprehensive reference text has been available previously to cover the wide breadth of this topic. The Editors have written the first three chapters to firmly introduce the reader to fundamental ML theories that can be used for chemical/biosensing. The subsequent chapters then cover the practical applications with contributions by various experts in the field. They show how ML and AI-based techniques can provide solutions for: 1) identifying and quantifying target molecules when specific receptors are unavailable 2) analyzing complex mixtures of target molecules, such as gut microbiome and soil microbiome 3) analyzing high-throughput and high-dimensional data, such as drug screening, molecular interaction, and environmental toxicant analysis, 4) analyzing complex data sets where fingerprinting approach is needed This book is written primarily for upper undergraduate students, graduate students, research staff, and faculty members at teaching and research universities and colleges who are working on chemical sensing, biosensing, analytical chemistry, analytical biochemistry, biomedical imaging, medical diagnostics, environmental monitoring, and agricultural applications. Presents the first comprehensive reference text on the use of ML and AI for chemical and biological sensing Provides a firm grounding in the fundamental theories on ML and AI before covering the practical applications with contributions by various experts in the field Includes a wide array of practical applications covered, including: E-nose, Raman, SERS, lens-free imaging, multi/hyperspectral imaging, NIR/optical imaging, receptor-free biosensing, paper microfluidics, single molecule analysis in biomedicine, in situ protein characterization, microbial population dynamics, and all-in-one sensor systems
