computational approaches in cheminformatics and bioinformatics

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Computational Approaches In Cheminformatics And Bioinformatics

Author : Rajarshi Guha
ISBN : 9781118131428
Genre : Science
File Size : 21. 37 MB
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A breakthrough guide employing knowledge that unites cheminformatics and bioinformatics as innovation for the future Bridging the gap between cheminformatics and bioinformatics for the first time, Computational Approaches in Cheminformatics and Bioinformatics provides insight on how to blend these two sciences for progressive research benefits. It describes the development and evolution of these fields, how chemical information may be used for biological relations and vice versa, the implications of these new connections, and foreseeable developments in the future. Using algorithms and domains as workflow tools, this revolutionary text drives bioinformaticians to consider chemical structure, and similarly, encourages cheminformaticians to consider large biological systems such as protein targets and networks. Computational Approaches in Cheminformatics and Bioinformatics covers: Data sources available for modelling and prediction purposes Developments of conventional Quantitative Structure-Activity Relationships (QSAR) Computational tools for manipulating chemical and biological data Novel ways of probing the interactions between small molecules and proteins Also including insight from public (NIH), academic, and industrial sources (Novartis, Pfizer), this book offers expert knowledge to aid scientists through industry and academic study. The invaluable applications for drug discovery, cellular and molecular biology, enzymology, and metabolism make Computational Approaches in Cheminformatics and Bioinformatics the essential guidebook for evolving drug discovery research and alleviating the issue of chemical control and manipulation of various systems.

Chemoinformatics And Advanced Machine Learning Perspectives Complex Computational Methods And Collaborative Techniques

Author : Lodhi, Huma
ISBN : 9781615209125
Genre : Computers
File Size : 89. 65 MB
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"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.

Machine Learning Methods For Channel Current Cheminformatics Biophysical Analysis And Bioinformatics

Author : Stephen Winters-Hilt
ISBN : UCSC:32106016064880
Genre : Computers
File Size : 69. 4 MB
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Bioinformatics A Primer

Author : P. Narayanan
ISBN : 9788122416107
Genre : Bioinformatics
File Size : 64. 57 MB
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Bioinformatics Is The Bridge Between Experimental Data In Diverse Biologically Related Disciplines And Extrapolation Of Information, By Computational Analysis, About How The Systems And Processes Function. The Central Aims Are : (I) Elucidation (By Experimental Methods) Of Structural Features Of The Biological Entities (Proteins, Nucleic Acids Etc.), (Ii) Application Of Computational Tools And Approaches To Study Of Information Content, Organization, And Processing In Biological Systems, (Iii) Application Of Medical And Health Data At The Molecular Level (Biomedinformatics), Annotation Of Structural And Chemical Characteristics In Molecular And Drug Design (Cheminformatics). Thus, It Requires Trans-Disciplinary Collaboration Between Biophysicists, Drug Chemists, Molecular Biologists, Biomedical And Computer-Aided Modeling Experts.Acquisition Of High-Throughput Biological Data (E.G. From The Genomic Projects) At Fast Rate Has Ushered In Computer-Intensive Data Analysis (In Silico Analysis). But, Considerable Algorithmic Complexity Of Biological Systems Requires A Vast Of Amount Of Detailed Information (Experimental And Computational) At The Cellular And Molecular Levels For Their Complete Description. Therefore, There Is A Need For Books In This Subject With Due Emphasis On Both Experimental As Well As Computational Aspects.With These Broad Objectives In Mind, The Material Contents Of This Book Are Organized Under-Molecular Biophysics, Experimental Methods Of Structure Elucidation, Database Search, Data Mining And Analysis, Computational Methods Of Structure Prediction, And Rational Molecular/Drug Design (Molecular Engineering) And Validation-, With Easy Interface Between These Areas And Various Chapters. Ample Tables And Figures Are Intended To Facilitate The Readers An Insight To The Structure-Function Features At The Molecular Level. Exercise Modules And Bibliography For Each Chapter, And Glossary Are Aimed At Providing The Reader Wider Perception And Insight To The Subject Matter, And Scientific And Technical Terms. Index Is Provided To Help An Easy Access To The Words And Topics To The Subject Matter.

Chemoinformatics And Computational Chemical Biology

Author : J├╝rgen Bajorath
ISBN : 1607618389
Genre : Science
File Size : 33. 98 MB
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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.


Author : Andrzej Polanski
ISBN : 9783540241669
Genre : Computers
File Size : 55. 37 MB
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This textbook presents mathematical models in bioinformatics and describes biological problems that inspire the computer science tools used to manage the enormous data sets involved. The first part of the book covers mathematical and computational methods, with practical applications presented in the second part. The mathematical presentation avoids unnecessary formalism, while remaining clear and precise. The book closes with a thorough bibliography, reaching from classic research results to very recent findings. This volume is suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on mathematical and computer science background.

Chemoinformatics Approaches To Virtual Screening

Author : Alexandre Varnek
ISBN : 1847558879
Genre : Mathematics
File Size : 23. 32 MB
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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 properties. Chemoinformatics addresses a broad range of problems in chemistry and biology; however, the most commonly known applications of chemoinformatics approaches have been arguably in the area of drug discovery where chemoinformatics tools have played a central role in the analysis and interpretation of structure-property data collected by the means of modern high throughput screening.Early stages in modern drug discovery often involved screening small molecules for their effects on a selected protein target or a model of a biological pathway. In the past fifteen years, innovative technologies that enable rapid synthesis and high throughput screening of large libraries of compounds have been adopted in almost all major pharmaceutical and biotech companies. As a result, there has been a huge increase in the number of compounds available on a routine basis to quickly screen for novel drug candidates against new targets/pathways. In contrast, such technologies have rarely become available to the academic research community, thus limiting its ability to conduct large scale chemical genetics or chemical genomics research. However, the landscape of publicly available experimental data collection methods for chemoinformatics has changed dramatically in very recent years. The term virtual screening is commonly associated with methodologies that rely on the explicit knowledge of three-dimensional structure of the target protein to identify potential bioactive compounds.Traditional docking protocols and scoring functions rely on explicitly defined three dimensional coordinates and standard definitions of atom types of both receptors and ligands. Albeit reasonably accurate in many cases, conventional structure based virtual screening approaches are relatively computationally inefficient, which has precluded them from screening really large compound collections. Significant progress has been achieved over many years of research in developing many structure based virtual screening approaches. This book is the first monograph that summarizes innovative applications of efficient chemoinformatics approaches towards the goal of screening large chemical libraries. The focus on virtual screening expands chemoinformatics beyond its traditional boundaries as a synthetic and data-analytical area of research towards its recognition as a predictive and decision support scientific discipline.The approaches discussed by the contributors to the monograph rely on chemoinformatics concepts such as: -representation of molecules using multiple descriptors of chemical structures -advanced chemical similarity calculations in multidimensional descriptor spaces -the use of advanced machine learning and data mining approaches for building quantitative and predictive structure activity models -the use of chemoinformatics methodologies for the analysis of drug-likeness and property prediction -the emerging trend on combining chemoinformatics and bioinformatics concepts in structure based drug discovery The chapters of the book are organized in a logical flow that a typical chemoinformatics project would follow - from structure representation and comparison to data analysis and model building to applications of structure-property relationship models for hit identification and chemical library design. It opens with the overview of modern methods of compounds library design, followed by a chapter devoted to molecular similarity analysis. Four sections describe virtual screening based on the using of molecular fragments, 2D pharmacophores and 3D pharmacophores.Application of fuzzy pharmacophores for libraries design is the subject of the next chapter followed by a chapter dealing with QSAR studies based on local molecular parameters. Probabilistic approaches based on 2D descriptors in assessment of biological activities are also described with an overview of the modern methods and software for ADME prediction. The book ends with a chapter describing the new approach of coding the receptor binding sites and their respective ligands in multidimensional chemical descriptor space that affords an interesting and efficient alternative to traditional docking and screening techniques. Ligand-based approaches, which are in the focus of this work, are more computationally efficient compared to structure-based virtual screening and there are very few books related to modern developments in this field. The focus on extending the experiences accumulated in traditional areas of chemoinformatics research such as Quantitative Structure Activity Relationships (QSAR) or chemical similarity searching towards virtual screening make the theme of this monograph essential reading for researchers in the area of computer-aided drug discovery.However, due to its generic data-analytical focus there will be a growing application of chemoinformatics approaches in multiple areas of chemical and biological research such as synthesis planning, nanotechnology, proteomics, physical and analytical chemistry and chemical genomics.

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