Download or read book An Introduction to Protein Informatics written by Karl-Heinz Zimmermann and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Protein informatics is a newer name for an already existing discipline. It encompasses the techniques used in bioinformatics and molecular modeling that are related to proteins. While bioinformatics is mainly concerned with the collection, organization, and analysis of biological data, molecular modeling is devoted to representation and manipulation of the structure of proteins. Protein informatics requires substantial prerequisites on computer science, mathematics, and molecular biology. The approach chosen here, allows a direct and rapid grasp on the subject starting from basic knowledge of algorithm design, calculus, linear algebra, and probability theory. An Introduction to Protein Informatics, a professional monograph will provide the reader a comprehensive introduction to the field of protein informatics. The text emphasizes mathematical and computational methods to tackle the central problems of alignment, phylogenetic reconstruction, and prediction and sampling of protein structure. An Introduction to Protein Informatics is designed for a professional audience, composed of researchers and practitioners within bioinformatics, molecular modeling, algorithm design, optimization, and pattern recognition. This book is also suitable as a graduate-level text for students in computer science, mathematics, and biomedicine.
Download or read book Protein Bioinformatics written by Ingvar Eidhammer and published by John Wiley & Sons. This book was released on 2004-02-13 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pairwise global alignment of sequences. Pairwise local alignment and database search. Statical analysis. Multiple global alignment and phylogenetic trees. Scoring matrices. Profiles. Sequence patterns. Structures and structure descriptions. Superposition and Dynamic programming. Geometric techniques. Clustering: Combining local similarities. Significance and assessment of structure comparisons. Multiple structure comparison. Protein structure classification. Structure prediction: Threading. Basics in mathematics, probability and algorithms. Introduction to molecular biology.
Download or read book Introduction to Protein DNA Interactions written by Gary Stormo and published by . This book was released on 2013 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the foundations of molecular biology is how the interactions of proteins with DNA control many aspects of gene expression. Since the mid-20th century discoveries of the lac repressor and operator and the competition between the cI and cro proteins for the same segment of DNA, we have learned an enormous amount about the interactions of proteins with DNA and their control of fundamental processes in the cell. Introduction to Protein-DNA Interactions: Structure, Thermodynamics, and Bioinformatics describes what we know about protein-DNA interactions from the complementary perspectives of molecular and structural biology and bioinformatics and how each perspective informs the others. A particular emphasis is on how insights from experimental work can be translated into specific computational approaches to create unified view of the field and a fuller understanding of protein-DNA interactions.
Download or read book Introduction to Protein Structure Prediction written by Huzefa Rangwala and published by John Wiley & Sons. This book was released on 2011-03-16 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.
Download or read book Mathematical Methods for Protein Structure Analysis and Design written by Concettina Guerra and published by Springer Science & Business Media. This book was released on 2003-06-25 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers collected in this volume reproduce contributions by leading sch- arstoaninternationalschoolandworkshopwhichwasorganizedandheldwith thegoaloftakinga snapshotofadiscipline undertumultuous growth. Indeed, the area of protein folding, docking and alignment is developing in response to needs for a mix of heterogeneous expertise spanning biology, chemistry, mathematics, computer science, and statistics, among others. Some of the problems encountered in this area are not only important for the scienti?c challenges they pose, but also for the opportunities they disclose intermsofmedicalandindustrialexploitation. Atypicalexampleiso?eredby protein-drug interaction (docking), a problem posing daunting computational problems at the crossroads of geometry, physics and chemistry, and, at the same time, a problem with unimaginable implications for the pharmacopoeia of the future. The schoolfocused on problems posed by the study of the mechanisms - hind protein folding, and explored di?erent ways of attacking these problems under objective evaluations of the methods. Together with a relatively small core of consolidated knowledge and tools, important re?ections were brought to this e?ort by studies in a multitude of directions and approaches. It is obviously impossible to predict which, if any, among these techniques will prove completely successful, but it is precisely the implicit dialectic among them that best conveys the current ?avor of the ?eld. Such unique diversity and richness inspired the format of the meeting, and also explains the slight departure of the present volume from the typical format in this series: the exposition of the current sediment is complemented here by a selection of quali?ed specialized contributions.
Download or read book Homology Molecular Modeling written by Rafael Trindade Maia and published by BoD – Books on Demand. This book was released on 2021-03-10 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Homology modeling is an extremely useful and versatile technique that is gaining more and more space and demand in research in computational and theoretical biology. This book, “Homology Molecular Modeling - Perspectives and Applications”, brings together unpublished chapters on this technique. In this book, 7 chapters are intimately related to the theme of molecular modeling, carefully selected and edited for academic and scientific readers. It is an indispensable read for anyone interested in the areas of bioinformatics and computational biology. Divided into 4 sections, the reader will have a didactic and comprehensive view of the theme, with updated and relevant concepts on the subject. This book was organized from researchers to researchers with the aim of spreading the fascinating area of molecular modeling by homology.
Download or read book Neural Networks and Genome Informatics written by C.H. Wu and published by Elsevier. This book was released on 2012-12-02 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive reference in the field of neural networks and genome informatics. The tutorial of neural network foundations introduces basic neural network technology and terminology. This is followed by an in-depth discussion of special system designs for building neural networks for genome informatics, and broad reviews and evaluations of current state-of-the-art methods in the field. This book concludes with a description of open research problems and future research directions.
Download or read book Bioinformatics Sequences Structures Phylogeny written by Asheesh Shanker and published by Springer. This book was released on 2018-10-13 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the concepts and approaches used for sequence, structure, and phylogenetic analysis. Starting with an introduction to the subject and intellectual property protection for bioinformatics, it guides readers through the latest sequencing technologies, sequence analysis, genomic variations, metagenomics, epigenomics, molecular evolution and phylogenetics, structural bioinformatics, protein folding, structure analysis and validation, drug discovery, reverse vaccinology, machine learning, application of R programming in biological data analysis, and the use of Linux in handling large data files.
Download or read book Biological Data Mining in Protein Interaction Networks written by Li, Xiao-Li and published by IGI Global. This book was released on 2009-05-31 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The goal of this book is to disseminate research results and best practices from cross-disciplinary researchers and practitioners interested in, and working on bioinformatics, data mining, and proteomics"--Provided by publisher.
Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Download or read book Concepts and Experimental Protocols of Modelling and Informatics in Drug Design written by Om Silakari and published by Academic Press. This book was released on 2020-11-05 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concepts and Experimental Protocols of Modelling and Informatics in Drug Design discusses each experimental protocol utilized in the field of bioinformatics, focusing especially on computer modeling for drug development. It helps the user in understanding the field of computer-aided molecular modeling (CAMM) by presenting solved exercises and examples. The book discusses topics such as fundamentals of molecular modeling, QSAR model generation, protein databases and how to use them to select and analyze protein structure, and pharmacophore modeling for drug targets. Additionally, it discusses data retrieval system, molecular surfaces, and freeware and online servers. The book is a valuable source for graduate students and researchers on bioinformatics, molecular modeling, biotechnology and several members of biomedical field who need to understand more about computer-aided molecular modeling. - Presents exercises with solutions to aid readers in validating their own protocol - Brings a thorough interpretation of results of each exercise to help readers compare them to their own study - Explains each parameter utilized in the algorithms to help readers understand and manipulate various features of molecules and target protein to design their study
Download or read book An Introduction To Protein Informatics written by Zimmermann Karl-Heinz and published by . This book was released on 2007-10-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nanopore Sequencing An Introduction written by Daniel Branton and published by World Scientific. This book was released on 2019-04-05 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an introductory text and laboratory manual to be used primarily in undergraduate courses. It is also useful for graduate students and research scientists who require an introduction to the theory and methods of nanopore sequencing. The book has clear explanations of the principles of this emerging technology, together with instructional material written by experts that describes how to use a MinION nanopore instrument for sequencing in research or the classroom.At Harvard University the book serves as a textbook and lab manual for a university laboratory course designed to intensify the intellectual experience of incoming undergraduates while exploring biology as a field of concentration. Nanopore sequencing is an ideal topic as a path to encourage students about the range of courses they will take in Biology by pre-emptively addressing the complaint about having to take a course in Physics or Maths while majoring in Biology. The book addresses this complaint by concretely demonstrating the range of topics — from electricity to biochemistry, protein structure, molecular engineering, and informatics — that a student will have to master in subsequent courses if he or she is to become a scientist who truly understands what his or her biology instrument is measuring when investigating biological phenomena.
Download or read book Introduction to Proteins written by Amit Kessel and published by CRC Press. This book was released on 2010-12-17 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the tools and techniques of structural biophysics assume greater roles in biological research and a range of application areas, learning how proteins behave becomes crucial to understanding their connection to the most basic and important aspects of life. With more than 350 color images throughout, Introduction to Proteins: Structure, Function, and Motion presents a unified, in-depth treatment of the relationship between the structure, dynamics, and function of proteins. Taking a structural–biophysical approach, the authors discuss the molecular interactions and thermodynamic changes that transpire in these highly complex molecules. The text incorporates various biochemical, physical, functional, and medical aspects. It covers different levels of protein structure, current methods for structure determination, energetics of protein structure, protein folding and folded state dynamics, and the functions of intrinsically unstructured proteins. The authors also clarify the structure–function relationship of proteins by presenting the principles of protein action in the form of guidelines. This comprehensive, color book uses numerous proteins as examples to illustrate the topics and principles and to show how proteins can be analyzed in multiple ways. It refers to many everyday applications of proteins and enzymes in medical disorders, drugs, toxins, chemical warfare, and animal behavior. Downloadable questions for each chapter are available at CRC Press Online.
Download or read book Machine Learning in Bioinformatics written by Yanqing Zhang and published by John Wiley & Sons. This book was released on 2009-02-23 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.
Download or read book Immunoinformatics written by Christian Schönbach and published by Springer Science & Business Media. This book was released on 2007-11-21 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: In contrast to existing books on immunoinformatics, this volume presents a cross-section of immunoinformatics research. The contributions highlight the interdisciplinary nature of the field and how collaborative efforts among bioinformaticians and bench scientists result in innovative strategies for understanding the immune system. Immunoinformatics is ideal for scientists and students in immunology, bioinformatics, microbiology, and many other disciplines.
Download or read book Protein Engineering and Design written by Sheldon J. Park and published by CRC Press. This book was released on 2009-09-25 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experimental protein engineering and computational protein design are broad but complementary strategies for developing proteins with altered or novel structural properties and biological functions. By describing cutting-edge advances in both of these fields, Protein Engineering and Design aims to cultivate a synergistic approach to protein science
