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Open Access Databases and Datasets for Drug Discovery

Open Access Databases and Datasets for Drug Discovery
Author: Antoine Daina
Publisher: John Wiley & Sons
Total Pages: 357
Release: 2023-12-26
Genre: Medical
ISBN: 3527348395

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Open Access Databases and Datasets for Drug Discovery Timely resource discussing the future of data-driven drug discovery and the growing number of open-source databases With an overview of 90 freely accessible databases and datasets on all aspects of drug design, development, and discovery, Open Access Databases and Datasets for Drug Discovery is a comprehensive guide to the vast amount of “free data” available to today’s pharmaceutical researchers. The applicability of open-source data for drug discovery and development is analyzed, and their usefulness in comparison with commercially available tools is evaluated. The most relevant databases for small molecules, drugs and druglike substances, ligand design, protein 3D structures (both experimental and calculated), and human drug targets are described in depth, including practical examples of how to access and work with the data. The first part is focused on databases for small molecules, followed by databases for macromolecular targets and diseases. The final part shows how to integrate various open-source tools into the academic and industrial drug discovery and development process. Contributed to and edited by experts with long-time experience in the field, Open Access Databases and Datasets for Drug Discovery includes information on: An extensive listing of open access databases and datasets for computer-aided drug design PubChem as a chemical database for drug discovery, DrugBank Online, and bioisosteric replacement for drug discovery supported by the SwissBioisostere database The Protein Data Bank (PDB) and macromolecular structure data supporting computer-aided drug design, and the SWISS-MODEL repository of 3D protein structures and models PDB-REDO in computational aided drug design (CADD), and using Pharos/TCRD for discovering druggable targets Unmatched in scope and thoroughly reviewing small and large open data sources relevant for rational drug design, Open Access Databases and Datasets for Drug Discovery is an essential reference for medicinal and pharmaceutical chemists, and any scientists involved in the drug discovery and drug development.


Artificial Intelligence in Drug Discovery

Artificial Intelligence in Drug Discovery
Author: Nathan Brown
Publisher: Royal Society of Chemistry
Total Pages: 425
Release: 2020-11-04
Genre: Computers
ISBN: 1839160543

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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.


Green's Dictionary of Slang (multi-volume set)

Green's Dictionary of Slang (multi-volume set)
Author: Jonathon Green
Publisher: Chambers
Total Pages: 0
Release: 2017-07-01
Genre: Reference
ISBN: 9780550104403

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The three volumes of Green's Dictionary of Slang demonstrate the sheer scope of a lifetime of research by Jonathon Green, the leading slang lexicographer of our time. A remarkable collection of this often reviled but endlessly fascinating area of the English language, it covers slang from the past five centuries right up to the present day, from all the different English-speaking countries and regions. Totaling 10.3 million words and over 53,000 entries, the collection provides the definitions of 100,000 words and over 413,000 citations. Every word and phrase is authenticated by genuine and fully-referenced citations of its use, giving the work a level of authority and scholarship unmatched by any other publication in this field. Winner of the Dartmouth Medal RUSA/ALA Outstanding Reference Source 2011 Booklist Editors' Choice Library Journal Best Reference 2011


Computer Applications in Drug Discovery and Development

Computer Applications in Drug Discovery and Development
Author: Puratchikody, A.
Publisher: IGI Global
Total Pages: 332
Release: 2018-11-23
Genre: Medical
ISBN: 1522573275

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With more restrictions upon animal experimentations, pharmaceutical industries are currently focusing on a new generation of experiments and technologies that are considerably more efficient and less controversial. The integration of computational and experimental strategies has led to the identification and development of promising compounds. Computer Applications in Drug Discovery and Development is a pivotal reference source that provides innovative research on the application of computers for discovering and designing new drugs in modern molecular biology and medicinal chemistry. While highlighting topics such as chemical structure databases and dataset utilization, this publication delves into the current panorama of drug discovery, where high drug failure rates are a major concern and properly designed virtual screening strategies can be a time-saving, cost-effective, and productive alternative. This book is ideally designed for chemical engineers, pharmacists, molecular biologists, students, researchers, and academicians seeking current research on the unexplored avenues and future perspectives of drug design.


Converging Pharmacy Science and Engineering in Computational Drug Discovery

Converging Pharmacy Science and Engineering in Computational Drug Discovery
Author: Tripathi, Rati Kailash Prasad
Publisher: IGI Global
Total Pages: 337
Release: 2024-04-22
Genre: Medical
ISBN:

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The world of pharmaceutical research is moving at lightning speed, and the age-old approach to drug discovery faces many challenges. It's a fascinating time to be on the cutting edge of medical innovation, but it's certainly not without its obstacles. The process of developing new drugs is often time-consuming, expensive, and fraught with uncertainty. Researchers are constantly seeking ways to streamline this process, reduce costs, and increase the success rate of bringing new drugs to market. One promising solution lies in the convergence of pharmacy science and engineering, particularly in computational drug discovery. Converging Pharmacy Science and Engineering in Computational Drug Discovery presents a comprehensive solution to these challenges by exploring the transformative synergy between pharmacy science and engineering. This book demonstrates how researchers can expedite the identification and development of novel therapeutic compounds by harnessing the power of computational approaches, such as sophisticated algorithms and modeling techniques. Through interdisciplinary collaboration, pharmacy scientists and engineers can revolutionize drug discovery, paving the way for more efficient and effective treatments. This book is an invaluable resource for pharmaceutical scientists, researchers, and engineers seeking to enhance their understanding of computational drug discovery. This book inspires future innovations by showcasing cutting-edge methodologies and innovative research at the intersection of pharmacy science and engineering. It contributes to the ongoing evolution of pharmaceutical research. It offers practical insights and solutions that will shape the future of drug discovery, making it essential reading for anyone involved in the pharmaceutical industry.


Computational Drug Discovery

Computational Drug Discovery
Author: Pooja A. Chawla
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 543
Release: 2024-10-07
Genre: Science
ISBN: 3111207595

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Computational methods and understanding computational models are important in modern drug discovery. The book focuses on computational approaches that can improve the development of in silico methodologies. It includes lead hit methods, docking algorithms, computational chiral compounds, structure-based drug design, GROMACS and NAMD, structural genomics, toxicity prediction, enzyme inhibitors and peptidomimetic therapeutics


Semantic Breakthrough in Drug Discovery

Semantic Breakthrough in Drug Discovery
Author: Bin Chen
Publisher: Springer
Total Pages: 0
Release: 2014-10-31
Genre: Mathematics
ISBN: 9783031794551

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The current drug development paradigm---sometimes expressed as, ``One disease, one target, one drug''---is under question, as relatively few drugs have reached the market in the last two decades. Meanwhile, the research focus of drug discovery is being placed on the study of drug action on biological systems as a whole, rather than on individual components of such systems. The vast amount of biological information about genes and proteins and their modulation by small molecules is pushing drug discovery to its next critical steps, involving the integration of chemical knowledge with these biological databases. Systematic integration of these heterogeneous datasets and the provision of algorithms to mine the integrated datasets would enable investigation of the complex mechanisms of drug action; however, traditional approaches face challenges in the representation and integration of multi-scale datasets, and in the discovery of underlying knowledge in the integrated datasets. The Semantic Web, envisioned to enable machines to understand and respond to complex human requests and to retrieve relevant, yet distributed, data, has the potential to trigger system-level chemical-biological innovations. Chem2Bio2RDF is presented as an example of utilizing Semantic Web technologies to enable intelligent analyses for drug discovery.Table of Contents: Introduction / Data Representation and Integration Using RDF / Data Representation and Integration Using OWL / Finding Complex Biological Relationships in PubMed Articles using Bio-LDA / Integrated Semantic Approach for Systems Chemical Biology Knowledge Discovery / Semantic Link Association Prediction / Conclusions / References / Authors' Biographies


Business Innovation

Business Innovation
Author: Vijay Pandiarajan
Publisher: Routledge
Total Pages: 356
Release: 2022-01-25
Genre: Business & Economics
ISBN: 1000538249

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This book provides an understanding of innovation models and why they are important in the business context, and considers sources of innovation and how to apply business frameworks using real-world examples of innovation-led businesses. After providing a solid background to the key concepts related to innovation models, the book looks at why innovation takes place and where the sources of innovation lie, from corporate research to crowd-sourced and government-funded initiatives. Innovation models across manufacturing, services and government are explored, as well as measuring innovation, and the impact of design thinking and lean enterprise principles on innovation and sustainability-driven imperatives. Offering a truly comprehensive and global approach, Business Innovation should be core or recommended reading for advanced undergraduate, postgraduate, MBA and Executive Education students studying Innovation Management, Strategic Management and Entrepreneurship.


Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays

Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays
Author: H. Gerhard Vogel
Publisher: Springer
Total Pages: 0
Release: 2013-02-27
Genre: Medical
ISBN: 9783642252396

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-A landmark in the continuously changing world of drugs -Essential reading for scientists and managers in the pharmaceutical industry involved in drug finding, drug development and decision making in the development process -Of use for government institutions and committees working on official guidelines for drug evaluation worldwide