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Chemoinformatics is broadly a scientific discipline encompassing the design, creation, organization, management, retrieval, analysis, dissemination, visualization and use of chemical information. It is distinct from other computational molecular modeling approaches in that it uses unique representations of chemical structures in the form of multiple chemical descriptors; has its own metrics for defining similarity and diversity of chemical compound libraries; and applies a wide array of statistical, data mining and machine learning techniques to very large collections of chemical compounds in order to establish robust relationships between chemical structure and its physical or biological pr...
Chemoinformatics strategies to improve drug discovery results With contributions from leading researchers in academia and the pharmaceutical industry as well as experts from the software industry, this book explains how chemoinformatics enhances drug discovery and pharmaceutical research efforts, describing what works and what doesn't. Strong emphasis is put on tested and proven practical applications, with plenty of case studies detailing the development and implementation of chemoinformatics methods to support successful drug discovery efforts. Many of these case studies depict groundbreaking collaborations between academia and the pharmaceutical industry. Chemoinformatics for Drug Discove...
This book presents pattern-based problem-solving methods for a variety of machine learning and data analysis problems. The methods are all based on techniques that exploit the power of group differences. They make use of group differences represented using emerging patterns (aka contrast patterns), which are patterns that match significantly different numbers of instances in different data groups. A large number of applications outside of the computing discipline are also included. Emerging patterns (EPs) are useful in many ways. EPs can be used as features, as simple classifiers, as subpopulation signatures/characterizations, and as triggering conditions for alerts. EPs can be used in gene ...
The Drug Discovery Handbook gives professionals a tool to facilitate drug discovery by bringing together, for the first time in one resource, a compendium of methods and techniques that need to be considered when developing new drugs. This comprehensive, practical guide presents an explanation of the latest techniques and methods in drug discovery, including: Genomics, proteomics, high-throughput screening, and systems biology Summaries of how these techniques and methods are used to discover new central nervous system agents, antiviral agents, respiratory drugs, oncology drugs, and more Specific approaches to drug discovery, including problems that are encountered, solutions to these problems, and limitations of various methods and techniques The thorough coverage and practical, scientifically valid problem-solving approach of Drug Discovery Handbook will serve as an invaluable aid in the complex task of developing new drugs.
The explosion in the generation of information parallels the explosion of computational resources. The use of computers to collect, store and manipulate chemical information is at the heart of chemoinformatics. These methodologies, whose main target thus far has been the pharmaceutical field, are general and can be applied to other types of chemical data sets, such as those containing food chemicals. While the use of chemical information methodologies to address food-related challenges is still in its infancy, interest is growing and will continue to do so as the methods prove useful, particularly for providing practical solutions to food industry challenges. Foodinformatics gives an overvie...
This book is a comprehensive exploration of the dynamic interplay between bioinformatics and artificial intelligence (AI) within the healthcare landscape. This book introduces readers to the foundational principles of bioinformatics and AI, elucidating their integration and collaborative potential. Bioinformatics and Beyond: AI Applications in Healthcare explores the transformative impact of data-driven insights, showcasing the applications of machine learning in diagnostics, personalized medicine, and genomic advancements. The book unveils the pivotal role AI plays in accelerating pharmaceutical research. Moreover, it addresses the practical implementation of AI in clinical decision support...
Over the past years, the chem(o)informatics field has further evolved and new application areas have opened up, for example, in the broadly defined area of chemical biology. In Chemoinformatics and Computational Chemical Biology, leading investigators bring together a detailed series of reviews and methods including, among others, system-directed approaches using small molecules, the design of target-focused compound libraries, the study of molecular selectivity, and the systematic analysis of target-ligand interactions. Furthermore, the book delves into similarity methods, machine learning, probabilistic approaches, fragment-based methods, as well as topics that go beyond the current chemoi...
Leading experts illustrate how sophisticated computational data mining techniques can impact contemporary drug discovery and development In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological, and clinical data is one of the greatest challenges facing the pharmaceutical industry. Pharmaceutical Data Mining brings together contributions from leading academic and industrial scientists, who address both the implementation of new data mining technologies and application issues in the industry. This accessible, comprehensive collection discusses important theoretical and practical aspects of pharmaceutical data mining, focusing on diverse approach...
"This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher.
An integrated overview of modern approaches to lead discovery Lead generation is increasingly seen as a distinct and success-determining phase of the drug discovery process. Over recent years, there have been major advances in the understanding of what constitutes a good lead compound and how to improve the chances of finding such a compound. Written by leading scientists and established opinion leaders from industry and academia, this book provides an authoritative overview of the field, as well as the theory, practice, and scope, of the principal Lead Generation Approaches in Drug Discovery, including: The evolution of the lead discovery process, key concepts, current challenges, and futur...