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Computational And Data Driven Chemistry Using Artificial Intelligence

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Computational and Data Driven Chemistry Using Artificial Intelligence

Computational and Data Driven Chemistry Using Artificial Intelligence Book
Author : Takashiro Akitsu
Publisher : Elsevier
Release : 2021-10-08
ISBN : 0128232722
Language : En, Es, Fr & De

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Book Description :

Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications. Drawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed. Provides an accessible introduction to the current state and future possibilities for AI in chemistry Explores how computational chemistry methods and approaches can both enhance and be enhanced by AI Highlights the interdisciplinary and broad applicability of AI tools across a wide range of chemistry fields

Computational and Data Driven Chemistry Using Artificial Intelligence

Computational and Data Driven Chemistry Using Artificial Intelligence Book
Author : Takashiro Akitsu
Publisher : Elsevier
Release : 2021-10-29
ISBN : 0128222492
Language : En, Es, Fr & De

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Book Description :

Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications. Drawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed. Provides an accessible introduction to the current state and future possibilities for AI in chemistry Explores how computational chemistry methods and approaches can both enhance and be enhanced by AI Highlights the interdisciplinary and broad applicability of AI tools across a wide range of chemistry fields

Applications of Computational Intelligence in Data Driven Trading

Applications of Computational Intelligence in Data Driven Trading Book
Author : Cris Doloc
Publisher : John Wiley & Sons
Release : 2019-10-29
ISBN : 1119550505
Language : En, Es, Fr & De

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Book Description :

“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.

Machine Learning in Chemistry

Machine Learning in Chemistry Book
Author : Edward O. Pyzer-Knapp,Teodoro Laino
Publisher : Unknown
Release : 2020-10-22
ISBN : 9780841235052
Language : En, Es, Fr & De

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Book Description :

Atomic-scale representation and statistical learning of tensorial properties -- Prediction of Mohs hardness with machine learning methods using compositional features -- High-dimensional neural network potentials for atomistic simulations -- Data-driven learning systems for chemical reaction prediction: an analysis of recent approaches -- Using machine learning to inform decisions in drug discovery : an industry perspective -- Cognitive materials discovery and onset of the 5th discovery paradigm.

Machine Learning in Chemistry

Machine Learning in Chemistry Book
Author : Hugh M Cartwright
Publisher : Royal Society of Chemistry
Release : 2020-07-15
ISBN : 1839160241
Language : En, Es, Fr & De

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Book Description :

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.

Chemistry at the Frontier with Physics and Computer Science

Chemistry at the Frontier with Physics and Computer Science Book
Author : Sergio Rampino
Publisher : Elsevier
Release : 2022-05-16
ISBN : 0323908667
Language : En, Es, Fr & De

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Book Description :

Chemistry at the Frontier with Physics and Computer Science: Theory and Computation shows how chemical concepts relate to their physical counterparts and can be effectively explored via computational tools. It provides a holistic overview of the intersection of these fields and offers practical examples on how to solve a chemical problem from a theoretical and computational perspective, going from theory to models, methods and implementation. Sections cover both sides of the Born-Oppenheimer approximation (nuclear dynamics and electronic structure), chemical reactions, chemical bonding, and cover theory to practice on three related physical problems (wavepacket dynamics, Hartree-Fock equations and electron-cloud redistribution). Drawing on the interdisciplinary knowledge of its expert author, this book provides a contemporary guide to theoretical and computational chemistry for all those working in chemical physics, physical chemistry and related fields. Combines a ‘big picture’ overview of chemistry as it relates to physics and computer science, including detailed guidance on tackling chemistry problems from both theoretical and computational perspectives Treats nuclear dynamics and electronic structure on the same footing in discussions of the Born-Oppenheimer approximation Includes examples of scientific programming in modern Fortran for problems related to the modeling of chemical reaction dynamics and the analysis of chemical bonding

Handbook of Materials Modeling

Handbook of Materials Modeling Book
Author : Sidney Yip
Publisher : Springer Science & Business Media
Release : 2007-11-17
ISBN : 1402032862
Language : En, Es, Fr & De

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Book Description :

The first reference of its kind in the rapidly emerging field of computational approachs to materials research, this is a compendium of perspective-providing and topical articles written to inform students and non-specialists of the current status and capabilities of modelling and simulation. From the standpoint of methodology, the development follows a multiscale approach with emphasis on electronic-structure, atomistic, and mesoscale methods, as well as mathematical analysis and rate processes. Basic models are treated across traditional disciplines, not only in the discussion of methods but also in chapters on crystal defects, microstructure, fluids, polymers and soft matter. Written by authors who are actively participating in the current development, this collection of 150 articles has the breadth and depth to be a major contributor toward defining the field of computational materials. In addition, there are 40 commentaries by highly respected researchers, presenting various views that should interest the future generations of the community. Subject Editors: Martin Bazant, MIT; Bruce Boghosian, Tufts University; Richard Catlow, Royal Institution; Long-Qing Chen, Pennsylvania State University; William Curtin, Brown University; Tomas Diaz de la Rubia, Lawrence Livermore National Laboratory; Nicolas Hadjiconstantinou, MIT; Mark F. Horstemeyer, Mississippi State University; Efthimios Kaxiras, Harvard University; L. Mahadevan, Harvard University; Dimitrios Maroudas, University of Massachusetts; Nicola Marzari, MIT; Horia Metiu, University of California Santa Barbara; Gregory C. Rutledge, MIT; David J. Srolovitz, Princeton University; Bernhardt L. Trout, MIT; Dieter Wolf, Argonne National Laboratory.

Artificial Intelligence in Education

Artificial Intelligence in Education Book
Author : Matthew N.O. Sadiku,Sarhan M. Musa,Uwakwe C. Chukwu
Publisher : iUniverse
Release : 2022-01-27
ISBN : 1663234345
Language : En, Es, Fr & De

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Book Description :

The quest for building an artificial brain developed in the fields of computer science and psychology. Artificial intelligence (AI), sometimes called machine intelligence, refers to intelligence demonstrated by machines, while the natural intelligence is the intelligence displayed by humans and animals. Typically, AI systems demonstrate at least some of the following human behaviors: planning, learning, reasoning, problem solving, knowledge representation, perception, speech recognition, decision-making, language translation, motion, manipulation, intelligence, and creativity. Artificial intelligence is an emerging technology which the educational sector can benefit from. In this book, we consider the applications of AI in key areas of education. Artificial intelligence in education (AIED) refers to the application of AI technologies in educational settings to facilitate teaching, learning, or decision making. AI will impact the education field in the areas of administration, instruction, and personalized, and individualized learning applications. In this book, AI is specifically applied in the following key educational sectors: education, natural sciences, social sciences, computer science, engineering, business, and medicine.

Reviews in Computational Chemistry

Reviews in Computational Chemistry Book
Author : Abby L. Parrill,Kenny B. Lipkowitz
Publisher : John Wiley & Sons
Release : 2016-03-09
ISBN : 1119157552
Language : En, Es, Fr & De

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Book Description :

The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on molecular modeling, such as computer-assisted molecular design (CAMD), quantum chemistry, molecular mechanics and dynamics, and quantitative structure-activity relationships (QSAR). This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. Topics in Volume 29 include: Noncovalent Interactions in Density-Functional Theory Long-Range Inter-Particle Interactions: Insights from Molecular Quantum Electrodynamics (QED) Theory Efficient Transition-State Modeling using Molecular Mechanics Force Fields for the Everyday Chemist Machine Learning in Materials Science: Recent Progress and Emerging Applications Discovering New Materials via a priori Crystal Structure Prediction Introduction to Maximally Localized Wannier Functions Methods for a Rapid and Automated Description of Proteins: Protein Structure, Protein Similarity, and Protein Folding

Artificial Intelligence in Drug Discovery

Artificial Intelligence in Drug Discovery Book
Author : Nathan Brown
Publisher : Royal Society of Chemistry
Release : 2020-11-11
ISBN : 1839160543
Language : En, Es, Fr & De

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Book Description :

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.

Computational Toxicology

Computational Toxicology Book
Author : Sean Ekins
Publisher : John Wiley & Sons
Release : 2007-07-27
ISBN : 9780470145883
Language : En, Es, Fr & De

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Book Description :

A comprehensive analysis of state-of-the-art molecular modeling approaches and strategies applied to risk assessment for pharmaceutical and environmental chemicals This unique volume describes how the interaction of molecules with toxicologically relevant targets can be predicted using computer-based tools utilizing X-ray crystal structures or homology, receptor, pharmacophore, and quantitative structure activity relationship (QSAR) models of human proteins. It covers the in vitro models used, newer technologies, and regulatory aspects. The book offers a complete systems perspective to risk assessment prediction, discussing experimental and computational approaches in detail, with: * An introduction to toxicology methods and an explanation of computational methods * In-depth reviews of QSAR methods applied to enzymes, transporters, nuclear receptors, and ion channels * Sections on applying computers to toxicology assessment in the pharmaceutical industry and in the environmental arena * Chapters written by leading international experts * Figures that illustrate computational models and references for further information This is a key resource for toxicologists and scientists in the pharmaceutical industry and environmental sciences as well as researchers involved in ADMET, drug discovery, and technology and software development.

Data Science in Chemistry

Data Science in Chemistry Book
Author : Thorsten Gressling
Publisher : Walter de Gruyter GmbH & Co KG
Release : 2020-11-23
ISBN : 3110630532
Language : En, Es, Fr & De

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Book Description :

The ever-growing wealth of information has led to the emergence of a fourth paradigm of science. This new field of activity – data science – includes computer science, mathematics and a given specialist domain. This book focuses on chemistry, explaining how to use data science for deep insights and take chemical research and engineering to the next level. It covers modern aspects like Big Data, Artificial Intelligence and Quantum computing.

Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering Book
Author : Jingzheng Ren,Weifeng Shen,Yi Man,Lichun DOng
Publisher : Elsevier
Release : 2021-06-05
ISBN : 012821743X
Language : En, Es, Fr & De

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Book Description :

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering

The Era of Artificial Intelligence Machine Learning and Data Science in the Pharmaceutical Industry

The Era of Artificial Intelligence  Machine Learning  and Data Science in the Pharmaceutical Industry Book
Author : Stephanie K. Ashenden
Publisher : Academic Press
Release : 2021-04-23
ISBN : 0128204494
Language : En, Es, Fr & De

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Book Description :

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

Emerging Trends in Data Driven Computing and Communications

Emerging Trends in Data Driven Computing and Communications Book
Author : Rajeev Mathur,C. P. Gupta,Vaibhav Katewa,Dharm Singh Jat,Neha Yadav
Publisher : Springer Nature
Release : 2021-09-27
ISBN : 9811639159
Language : En, Es, Fr & De

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Book Description :

This book includes best selected, high-quality research papers presented at International Conference on Data Driven Computing and IoT (DDCIoT 2021) organized jointly by Geetanjali Institute of Technical Studies (GITS), Udaipur, and Rajasthan Technical University, Kota, India, during March 20–21, 2021. This book presents influential ideas and systems in the field of data driven computing, information technology, and intelligent systems.

Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines

Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines Book
Author : Jihad Badra,Pinaki Pal,Yuanjiang Pei,Sibendu Som
Publisher : Elsevier
Release : 2022-01-21
ISBN : 032388458X
Language : En, Es, Fr & De

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Book Description :

Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines summarizes recent developments in Artificial Intelligence (AI)/Machine Learning (ML) and data driven optimization and calibration techniques for internal combustion engines. The book covers AI/ML and data driven methods to optimize fuel formulations and engine combustion systems, predict cycle to cycle variations, and optimize after-treatment systems and experimental engine calibration. It contains all the details of the latest optimization techniques along with their application to ICE, making it ideal for automotive engineers, mechanical engineers, OEMs and R&D centers involved in engine design. Provides AI/ML and data driven optimization techniques in combination with Computational Fluid Dynamics (CFD) to optimize engine combustion systems Features a comprehensive overview of how AI/ML techniques are used in conjunction with simulations and experiments Discusses data driven optimization techniques for fuel formulations and vehicle control calibration

Data Science in Chemistry

Data Science in Chemistry Book
Author : Thorsten Gressling
Publisher : Walter de Gruyter GmbH & Co KG
Release : 2020-11-23
ISBN : 3110629453
Language : En, Es, Fr & De

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Book Description :

The ever-growing wealth of information has led to the emergence of a fourth paradigm of science. This new field of activity – data science – includes computer science, mathematics and a given specialist domain. This book focuses on chemistry, explaining how to use data science for deep insights and take chemical research and engineering to the next level. It covers modern aspects like Big Data, Artificial Intelligence and Quantum computing.

Understanding Protein Dynamics Binding and Allostery for Drug Design

Understanding Protein Dynamics  Binding and Allostery for Drug Design Book
Author : Guang Hu,Pemra Doruker,Hongchun Li,Ebru Demet Akten
Publisher : Frontiers Media SA
Release : 2021-06-08
ISBN : 2889668487
Language : En, Es, Fr & De

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Book Description :

Download Understanding Protein Dynamics Binding and Allostery for Drug Design book written by Guang Hu,Pemra Doruker,Hongchun Li,Ebru Demet Akten, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Advances in Artificial Intelligence and Applied Cognitive Computing

Advances in Artificial Intelligence and Applied Cognitive Computing Book
Author : Hamid R. Arabnia,Ken Ferens,David de la Fuente,Elena B. Kozerenko,José Angel Olivas Varela,Fernando G. Tinetti
Publisher : Springer Nature
Release : 2021
ISBN : 3030702960
Language : En, Es, Fr & De

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Book Description :

The book presents the proceedings of two conferences: The 22nd International Conference on Artificial Intelligence (ICAI'20) and The 4th International Conference on Applied Cognitive Computing (ACC'20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020, and are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Topics include: deep learning; neural networks; brain models; cognitive science; natural language processing; fuzzy logic and soft computing (ICAI) and novel computationally intelligent algorithms; bio inspired cognitive algorithms; modeling human brain processing systems (ACC); and more. Authors include academics, researchers, and professionals. Presents the proceedings of two conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the tracks: artificial intelligence and applied cognitive computing; Features papers from the 22nd International Conference on AI (ICAI'20) and the 4th International Conference on Applied Cognitive Computing (ACC'20).

Polypharmacology

Polypharmacology Book
Author : Zhiguo Wang,Baofeng Yang
Publisher : Springer Nature
Release : 2022-08-01
ISBN : 3031049985
Language : En, Es, Fr & De

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Book Description :

There is a growing interest in unmet needs for the development of a new discipline in drug discovery and in university education on polypharmacology. However, there has not been a book with the comprehensive compilation of basic knowledge and advanced methodology that is needed. This book aims to meet the needs making Polypharmacology a new sub-discipline of Pharmacology, not only being a hot area of pharmacological research and education but also a new paradigm for drug discovery. It contains the contents covering the entire scope of Polypharmacology including systemic in-depth exposition of basic knowledge, novel concepts, innovative technologies, and translational and clinical applications by showcasing state-of-the-art strategies and step-by-step instructions of cutting-edge methods. The contents of this book targets broad readerships including scientists in pharmacology research and drug development, and university teachers and graduates in medical school or school of pharmacy.