Artificial Intelligence in Organic Chemistry SST
Author: David Rogers
Publisher:
Published: 1984
Total Pages: 304
ISBN-13:
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Author: David Rogers
Publisher:
Published: 1984
Total Pages: 304
ISBN-13:
DOWNLOAD EBOOKAuthor: Tuan D. Pham
Publisher: Springer Nature
Published: 2021-07-12
Total Pages: 373
ISBN-13: 303069951X
DOWNLOAD EBOOKArtificial 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.
Author: Markus C. Hemmer
Publisher: CRC Press
Published: 2007-12-13
Total Pages: 418
ISBN-13: 1420053248
DOWNLOAD EBOOKExpert systems allow scientists to access, manage, and apply data and specialized knowledge from various disciplines to their own research. Expert Systems in Chemistry Research explains the general scientific basis and computational principles behind expert systems and demonstrates how they can improve the efficiency of scientific workflows
Author: Committee on Mathematical Challenges from Computational Chemistry
Publisher: National Academies Press
Published: 1995-04-12
Total Pages: 144
ISBN-13: 0309560640
DOWNLOAD EBOOKComputational methods are rapidly becoming major tools of theoretical, pharmaceutical, materials, and biological chemists. Accordingly, the mathematical models and numerical analysis that underlie these methods have an increasingly important and direct role to play in the progress of many areas of chemistry. This book explores the research interface between computational chemistry and the mathematical sciences. In language that is aimed at non-specialists, it documents some prominent examples of past successful cross-fertilizations between the fields and explores the mathematical research opportunities in a broad cross-section of chemical research frontiers. It also discusses cultural differences between the two fields and makes recommendations for overcoming those differences and generally promoting this interdisciplinary work.
Author: Kenny B. Lipkowitz
Publisher: John Wiley & Sons
Published: 2003-04-14
Total Pages: 384
ISBN-13: 0471461423
DOWNLOAD EBOOKSeit vielen Jahren praxisbewährt! Auch dieser 18. Band der Reihe Reviews in Computational Chemistry gibt Studenten und Forschern einen Einblick in Rechenverfahren, die sie anwenden wollen, ohne daß die theoretischen Grundlagen zu ihrem Arbeitsgebiet gehören. Das methodische Spektrum umfaßt Molecular Modeling, Quantenchemie, CAMD, QSAR, Molekülmechanik und -dynamik. Mit einem Autoren- und einem Stichwortverzeichnis sowie einer ausführlichen Softwareliste, die Hunderte von Programmen, Dienstleistungen und Anbietern umfaßt.
Author: Philip Judson
Publisher: Royal Society of Chemistry
Published: 2019-02-07
Total Pages: 298
ISBN-13: 1788014715
DOWNLOAD EBOOKThis new edition has been thoroughly revised and updated to reflect the advances in using knowledge-based expert systems for chemistry.
Author: Jon Paul Janet
Publisher: American Chemical Society
Published: 2020-05-28
Total Pages: 189
ISBN-13: 0841299005
DOWNLOAD EBOOKRecent 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
Author: Kenny B. Lipkowitz
Publisher: John Wiley & Sons
Published: 2009-09-22
Total Pages: 443
ISBN-13: 0470126051
DOWNLOAD EBOOKThis book is an account of current developments in computational chemistry, a new multidisciplinary area of research. Experts in computational chemistry, the editors use and develop techniques for computer-assisted molecular design. The core of the text itself deals with techniques for computer-assisted molecular design. The book is suitable for both beginners and experts. In addition, protocols and software for molecular recognition and the relationship between structure and biological activity of drug molecules are discussed in detail. Each chapter includes a mini-tutorial, as well as discussion of advanced topics. Special Feature: The appendix to this book contains an extensive list of available software for molecular modeling.
Author: Kenny B. Lipkowitz
Publisher: John Wiley & Sons
Published: 2009-09-22
Total Pages: 441
ISBN-13: 0470126116
DOWNLOAD EBOOKThis is the seventh volume in the successful series designed to help the chemistry community keep current with the many new developments in computational techniques. The writing style is refreshingly pedagogical and non-mathematical, allowing students and researchers access to computational methods outside their immediate area of expertise. Each invited author approaches a topic with the aim of helping the reader understand the material, solve problems, and locate key references quickly.
Author: Hugh M. Cartwright
Publisher: Royal Society of Chemistry
Published: 2020-07-15
Total Pages: 564
ISBN-13: 1788017897
DOWNLOAD EBOOKProgress 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.