The use of computers and software tools in biochemistry (biology) has led to a deep revolution in basic sciences and medicine. Bioinformatics and systems biology are the direct results of this revolution. With the involvement of computers, software tools, and internet services in scientific disciplines comprising biology and chemistry, new terms, technologies, and methodologies appeared and established. Bioinformatic software tools, versatile databases, and easy internet access resulted in the occurrence of computational biology and chemistry. Today, we have new types of surveys and laboratories including "in silico studies" and "dry labs" in which bioinformaticians conduct their investigations to gain invaluable outcomes. These features have led to 3-dimensioned illustrations of different molecules and complexes to get a better understanding of nature.
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 chemoinformatics spectrum, such as knowledge-based modeling of G protein-coupled receptor structures and computational design of siRNA libraries. As a volume in the highly successful Methods in Molecular BiologyTM series, this collection provides detailed descriptions and implementation advice that are exceedingly relevant for basic researchers and practitioners in this highly interdisciplinary research and development area. Cutting-edge and unambiguous, Chemoinformatics and Computational Chemical Biology serves as an ideal guide for experts and newcomers alike to this vital and dynamic field of study.
Computational Chemistry Methodology in Structural Biology and Materials Sciences provides a selection of new research in theoretical and experimental chemistry, focusing on topics in the materials science and biological activity. Part 1, on Computational Chemistry Methodology in Biological Activity, of the book emphasizes presents new developments in the domain of theoretical and computational chemistry and its applications to bioactive molecules. It looks at various aspects of density functional theory and other issues. Part 2, on Computational Chemistry Methodology in Materials Science, presents informative new research on computational chemistry as applied to materials science. The wide range of topics regarding the application of theoretical and experimental chemistry and materials science and biological domain will be valuable in the context of addressing contemporary research problems.
This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.
Exploring current themes in modern computational and membrane protein biophysics, this book presents a comprehensive account of the fundamental principles underlying different methods and techniques used to describe the intriguing mechanisms by which membrane proteins function. The book discusses the experimental approaches employed to study these proteins, with chapters reviewing recent crucial structural advances that have allowed computational biophysicists to discern how these molecular machines work. The book then explores what computational methods are available to researchers and what these have taught us about three key families of membrane proteins: ion channels, transporters and receptors. The book is ideal for researchers in computational chemistry and computational biophysics.
The book offers new concepts and ideas that broaden reader’s perception of modern science. Internationally established experts present the inspiring new science of complexity, which discovers new general laws covering wide range of science areas. The book offers a broader view on complexity based on the expertise of the related areas of chemistry, biochemistry, biology, ecology, and physics. Contains methodologies for assessing the complexity of systems that can be directly applied to proteomics and genomics, and network analysis in biology, medicine, and ecology.
The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology of
Groundbreaking, long-ranging research in this emergent field that enables solutions to complex biological problems Computational systems biology is an emerging discipline that is evolving quickly due to recent advances in biology such as genome sequencing, high-throughput technologies, and the recent development of sophisticated computational methodologies. Elements of Computational Systems Biology is a comprehensive reference covering the computational frameworks and techniques needed to help research scientists and professionals in computer science, biology, chemistry, pharmaceutical science, and physics solve complex biological problems. Written by leading experts in the field, this practical resource gives detailed descriptions of core subjects, including biological network modeling, analysis, and inference; presents a measured introduction to foundational topics like genomics; and describes state-of-the-art software tools for systems biology. Offers a coordinated integrated systems view of defining and applying computational and mathematical tools and methods to solving problems in systems biology Chapters provide a multidisciplinary approach and range from analysis, modeling, prediction, reasoning, inference, and exploration of biological systems to the implications of computational systems biology on drug design and medicine Helps reduce the gap between mathematics and biology by presenting chapters on mathematical models of biological systems Establishes solutions in computer science, biology, chemistry, and physics by presenting an in-depth description of computational methodologies for systems biology Elements of Computational Systems Biology is intended for academic/industry researchers and scientists in computer science, biology, mathematics, chemistry, physics, biotechnology, and pharmaceutical science. It is also accessible to undergraduate and graduate students in machine learning, data mining, bioinformatics, computational biology, and systems biology courses.
Computational Chemistry Using the PC, Third Edition takes the reader from a basic mathematical foundation to beginning research-level calculations, avoiding expensive or elaborate software in favor of PC applications. Geared towards an advanced undergraduate or introductory graduate course, this Third Edition has revised and expanded coverage of molecular mechanics, molecular orbital theory, molecular quantum chemistry, and semi-empirical and ab initio molecular orbital approaches. With significant changes made to adjust for improved technology and increased computer literacy, Computational Chemistry Using the PC, Third Edition gives its readers the tools they need to translate theoretical principles into real computational problems, then proceed to a computed solution. Students of computational chemistry, as well as professionals interested in updating their skills in this fast-moving field, will find this book to be an invaluable resource.
