Computational biology drives discovery through its use of high-throughput informatics approaches. This book provides a road map of the current drug development process and how computational biology approaches play a critical role across the entire drug discovery pipeline. Through the use of previously unpublished, real-life case studies the impact of a range of computational approaches are discussed at various phases of the pipeline. Additionally, a focus section provides innovative visualisation approaches, from both the drug discovery process as well as from other fields that utilise large datasets, recognising the increasing use of such technology. Serving the needs of early career and more experienced scientists, this up-to-date reference provides an essential introduction to the process and background of drug discovery, highlighting how computational researchers can contribute to that pipeline.

This new book takes an in-depth look at the emerging and prospective field of computational biology and bioinformatics, which possesses the ability to analyze large accumulated biological data collected from sequence analysis of proteins and genes and cell population with an aim to make new predictions pertaining to drug discovery and new biology. The book explains the basic methodology associated with a bioinformatics and computational approach in drug designing. It then goes on to cover the implementation of computational programming, bioinformatics, pharmacophore modeling, biotechnological techniques, and pharmaceutical chemistry in designing drugs. The major advantage of intervention of computer language or programming is to cut down the number of steps and costs in the field of drug designing, reducing the repeating steps and saving time in screening the potent component for drug or vaccine designing. The book describes algorithms used for drug designing and the use of machine learning and AI in drug delivery and disease diagnosis, which are valuable in clinical decision-making. The implementation of robotics in different diseases like stroke, cancer, COVID-19, etc. is also addressed. Topics include machine learning, AI, databases in drug design, molecular docking, bioinformatics tools, target-based drug design, and immunoinformatics, chemoinformatics, and nanoinformatics in drug design. Drug repurposing in drug design in general as well as for specific diseases, including cancer, Alzheimer’s disease, tuberculosis, COVID-19, etc., is also addressed in depth.

Recent advances in drug discovery have been rapid. The second edition of Bioinformatics and Drug Discovery has been completely updated to include topics that range from new technologies in target identification, genomic analysis, cheminformatics, protein analysis, and network or pathway analysis. Each chapter provides an extended introduction that describes the theory and application of the technology. In the second part of each chapter, detailed procedures related to the use of these technologies and software have been incorporated. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Bioinformatics and Drug Discovery, Second Edition seeks to aid scientists in the further study of the rapidly expanding field of drug discovery.

Chemoinformatics and Bioinformatics in the Pharmaceutical Sciences brings together two very important fields in pharmaceutical sciences that have been mostly seen as diverging from each other: chemoinformatics and bioinformatics. As developing drugs is an expensive and lengthy process, technology can improve the cost, efficiency and speed at which new drugs can be discovered and tested. This book presents some of the growing advancements of technology in the field of drug development and how the computational approaches explained here can reduce the financial and experimental burden of the drug discovery process. This book will be useful to pharmaceutical science researchers and students who need basic knowledge of computational techniques relevant to their projects. Bioscientists, bioinformaticians, computational scientists, and other stakeholders from industry and academia will also find this book helpful. Provides practical information on how to choose and use appropriate computational tools Presents the wide, intersecting fields of chemo-bio-informatics in an easily-accessible format Explores the fundamentals of the emerging field of chemoinformatics and bioinformatics

This book has originated from Practical class on Genomics & Proteomics that are offered to students of Computational Biology, Bangalore University of Bangalore. The idea to write a book on Computational Biology was born during the preparations of these practical where I realized that it is extremely difficult to achieve an overview of the area of Drug Discovery and to follow the progress of this field. This is the first book in 2015 and was written in English .Computational Biology is a major topic in modern medical, Life science and pharmacological research and is of central importance in the computational biology science. Accordingly, The enormous increase in data on Drug Designing has led me to leave out the practical on Computational Biology and. This topic has since evolved into a huge research area of its own that could not be considered adequately within this book. My knowledge of Drug Designing practical has exploded in the past 5 years, Bioinformatics could be treated here with the same thoroughness. It is the aim of the present book to describe the Bioinformatics practical approach for life science students.

With a DVD of color figures, Clustering in Bioinformatics and Drug Discovery provides an expert guide on extracting the most pertinent information from pharmaceutical and biomedical data. It offers a concise overview of common and recent clustering methods used in bioinformatics and drug discovery.Setting the stage for subsequent material, the firs

This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs.