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Deep Learning In Drug Design

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Deep Learning In Drug Design

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Author : Qifeng Bai
language : en
Publisher: Academic Press
Release Date : 2025-10-01

Deep Learning In Drug Design written by Qifeng Bai and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-01 with Medical categories.

Deep Learning in Drug Design: Methods and Applications summarizes the most recent methods, and technological advances of deep learning for drug design, which mainly consists of molecular representations, the architectures of deep learning, geometric deep learning, large models, etc., as well as deep learning applications in various aspects of drug design. This book offers a comprehensive academic overview of deep learning in drug design. It begins with molecular representations, CNNs, GNNs, Transformers, generative models, explainable AI, large models, etc. Next, it covers deep learning applications like protein structure prediction, molecular interactions, ADMET prediction, antibody design, and so on. Finally, a separate chapter is dedicated to the introduction of the ethics and regulation of artificial intelligence in drug design. This book is ideal for readers aiming to learn and implement deep learning methods and applications in drug design and related fields. Deep Learning in Drug Design: Methods and Applications is particularly helpful to undergraduate, graduate, and doctoral students in need of a practical guide to the principles of the discipline. Established researchers in the area will benefit from the detailed case studies and algorithms presented.

Artificial Intelligence In Drug Discovery

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Author : Nathan Brown
language : en
Publisher: Royal Society of Chemistry
Release Date : 2020-11-04

Artificial Intelligence In Drug Discovery written by Nathan Brown and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-04 with Computers categories.

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.

Artificial Intelligence And Machine Learning In Drug Design And Development

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Author : Abhirup Khanna
language : en
Publisher: John Wiley & Sons
Release Date : 2024-06-21

Artificial Intelligence And Machine Learning In Drug Design And Development written by Abhirup Khanna and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-21 with Computers categories.

The book is a comprehensive guide that explores the use of artificial intelligence and machine learning in drug discovery and development covering a range of topics, including the use of molecular modeling, docking, identifying targets, selecting compounds, and optimizing drugs. The intersection of Artificial Intelligence (AI) and Machine Learning (ML) within the field of drug design and development represents a pivotal moment in the history of healthcare and pharmaceuticals. The remarkable synergy between cutting-edge technology and the life sciences has ushered in a new era of possibilities, offering unprecedented opportunities, formidable challenges, and a tantalizing glimpse into the future of medicine. AI can be applied to all the key areas of the pharmaceutical industry, such as drug discovery and development, drug repurposing, and improving productivity within a short period. Contemporary methods have shown promising results in facilitating the discovery of drugs to target different diseases. Moreover, AI helps in predicting the efficacy and safety of molecules and gives researchers a much broader chemical pallet for the selection of the best molecules for drug testing and delivery. In this context, drug repurposing is another important topic where AI can have a substantial impact. With the vast amount of clinical and pharmaceutical data available to date, AI algorithms find suitable drugs that can be repurposed for alternative use in medicine. This book is a comprehensive exploration of this dynamic and rapidly evolving field. In an era where precision and efficiency are paramount in drug discovery, AI and ML have emerged as transformative tools, reshaping the way we identify, design, and develop pharmaceuticals. This book is a testament to the profound impact these technologies have had and will continue to have on the pharmaceutical industry, healthcare, and ultimately, patient well-being. The editors of this volume have assembled a distinguished group of experts, researchers, and thought leaders from both the AI, ML, and pharmaceutical domains. Their collective knowledge and insights illuminate the multifaceted landscape of AI and ML in drug design and development, offering a roadmap for navigating its complexities and harnessing its potential. In each section, readers will find a rich tapestry of knowledge, case studies, and expert opinions, providing a 360-degree view of AI and ML’s role in drug design and development. Whether you are a researcher, scientist, industry professional, policymaker, or simply curious about the future of medicine, this book offers 19 state-of-the-art chapters providing valuable insights and a compass to navigate the exciting journey ahead. Audience The book is a valuable resource for a wide range of professionals in the pharmaceutical and allied industries including researchers, scientists, engineers, and laboratory workers in the field of drug discovery and development, who want to learn about the latest techniques in machine learning and AI, as well as information technology professionals who are interested in the application of machine learning and artificial intelligence in drug development.

Drug Design Using Machine Learning

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Author : Inamuddin
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-22

Drug Design Using Machine Learning written by Inamuddin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-22 with Medical categories.

DRUG DESIGN USING MACHINE LEARNING The use of machine learning algorithms in drug discovery has accelerated in recent years and this book provides an in-depth overview of the still-evolving field. The objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments. This excellent overview Provides a broad synopsis of machine learning and artificial intelligence applications to the advancement of drugs; Details the use of molecular recognition for drug development through various mathematical models; Highlights classical as well as machine learning-based approaches to study target-drug interactions in the field of drug discovery; Explores computer-aided technics for prediction of drug effectiveness and toxicity. Audience The book will be useful for information technology professionals, pharmaceutical industry workers, engineers, university researchers, medical practitioners, and laboratory workers who have a keen interest in the area of machine learning and artificial intelligence approaches applied to drug advancements.

Artificial Intelligence And Machine Learning In Drug Design And Development

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Author : Abhirup Khanna
language : en
Publisher: John Wiley & Sons
Release Date : 2024-07-18

Machine Learning For Drug Discovery

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Author : Marcelo C. R. Melo
language : en
Publisher: American Chemical Society
Release Date : 2022-03-11

Machine Learning For Drug Discovery written by Marcelo C. R. Melo and has been published by American Chemical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Computers categories.

Machine Learning for Drug Discovery is designed to suit the needs of graduate students, advanced undergraduates, chemists or biologists otherwise new to this research domain with minimal previous exposure to Machine Learning (ML) methods, or computational scientists with minimal exposure to medicinal chemistry. The e-book covers basic algorithmic theory, data representation methods, and generative modeling at a high level. The authors spotlight antibiotic discovery as a case study in ML for drug development and discuss diverse applications in drug-likeness prediction, antimicrobial resistance, and areas for future inquiry. For a more dynamic learning experience, open-source code demonstrations in Python are included.

Advances In Deep Learning And Bioinformatics

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Author : Dr. Monish Mukul Das
language : en
Publisher: Chyren Publication
Release Date : 2025-02-04

Advances In Deep Learning And Bioinformatics written by Dr. Monish Mukul Das and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-04 with Antiques & Collectibles categories.

Revolutionizing Drug Discovery Cutting Edge Computational Techniques

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Author :
language : en
Publisher: Academic Press
Release Date : 2025-04-03

Revolutionizing Drug Discovery Cutting Edge Computational Techniques written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-03 with Medical categories.

Revolutionizing Drug Discovery: Cutting-Edge Computational Techniques, Volume 103 is an essential guide for professionals, researchers, and students in the pharmaceutical and biotech industries, providing an in-depth look at how computational methods transform drug development. Chapters in this new release include Innovative Computational Approaches in Drug Discovery and Design, Advanced Molecular Modeling of Proteins: Methods, Breakthroughs, and Future Prospects, Predictive Cavity and Binding Site Identification: Techniques and Applications, ADMET Tools in the Digital Era: Applications and Limitations, Essential Database Resources for Modern Drug Discovery, Deep Learning for Drug Design and Development, and much more.Other sections cover Molecular Docking and Structure-Based Drug Design: From Theory to Practice, Molecular Dynamics Simulations: Insights into Protein and Protein-Ligand Interactions, Targeting Disease: Computational Approaches for Drug Target Identification, High-throughput computational Screening for Lead Discovery and Development, Harnessing Machine Learning for Rational Drug Design, Identifying Novel Drug Targets with Computational Precision, Computational Exploration of Viral Cell Membrane Structures for Identifying Novel Therapeutic Target, and many more interesting topics. - Offers expert insights from leading authorities on computational techniques in drug discovery, ensuring readers gain accurate, cutting-edge knowledge - Includes illustrative graphics and case studies to enhance comprehension and engagement for readers across disciplines - Provides forward-looking perspectives on the role of computational methods in drug development, highlighting both current advancements and future trends

Drug Discovery And Development Explained Introductory Notes For The General Public

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Author : Bruno Villoutreix
language : en
Publisher: Frontiers Media SA
Release Date : 2024-12-11

Drug Discovery And Development Explained Introductory Notes For The General Public written by Bruno Villoutreix and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-11 with Medical categories.

Drug discovery and development involve complex processes, highly integrated interdisciplinary research, and collaborations between academic groups and the private sector. It is a long and resource-intensive endeavor characterized by a high attrition rate. Yet new strategies are being explored, aiming at accelerating the development of novel treatments, from the combination of artificial intelligence with cutting-edge experimental approaches, and the development of novel types of therapeutic agents to personalized medicine. Because drug discovery and development is a vast field with many stakeholders and potential conflicts of interest, it is important that the general public gains basic knowledge about the main concepts to be able to make informed healthcare decisions for themselves and family members, understand discussions in the news and social networks or proposals from policymakers and politicians. Furthermore, people are directly affected by the field, as patients seeking novel and better treatments, as volunteers in clinical trials, or as members of patient organizations. Building public knowledge and understanding about the field of drug discovery and development will also help to address growing public concerns about how health data should be collected and used.

Cheminformatics Qsar And Machine Learning Applications For Novel Drug Development

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Author : Kunal Roy
language : en
Publisher: Elsevier
Release Date : 2023-05-23

Cheminformatics Qsar And Machine Learning Applications For Novel Drug Development written by Kunal Roy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-23 with Medical categories.

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book.The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates. - Presents chemometrics, cheminformatics and machine learning methods under a single reference - Showcases the different structure-based, ligand-based and machine learning tools currently used in drug design - Highlights special topics of computational drug design and available tools and databases

Deep Learning In Drug Design

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