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Author: Dev Bukhsh Singh
Publisher: Academic Press
ISBN: 0323900054
Category : Medical
Languages : en
Pages : 512
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Book Description
Bioinformatics: Methods and Applications provides a thorough and detailed description of principles, methods, and applications of bioinformatics in different areas of life sciences. It presents a compendium of many important topics of current advanced research and basic principles/approaches easily applicable to diverse research settings. The content encompasses topics such as biological databases, sequence analysis, genome assembly, RNA sequence data analysis, drug design, and structural and functional analysis of proteins. In addition, it discusses computational approaches for vaccine design, systems biology and big data analysis, and machine learning in bioinformatics.It is a valuable source for bioinformaticians, computer biologists, and members of biomedical field who needs to learn bioinformatics approaches to apply to their research and lab activities. - Covers basic and more advanced developments of bioinformatics with a diverse and interdisciplinary approach to fulfill the needs of readers from different backgrounds - Explains in a practical way how to decode complex biological problems using computational approaches and resources - Brings case studies, real-world examples and several protocols to guide the readers with a problem-solving approach
Author: Dev Bukhsh Singh
Publisher: Academic Press
ISBN: 0323900054
Category : Medical
Languages : en
Pages : 512
Get Book Here
Book Description
Bioinformatics: Methods and Applications provides a thorough and detailed description of principles, methods, and applications of bioinformatics in different areas of life sciences. It presents a compendium of many important topics of current advanced research and basic principles/approaches easily applicable to diverse research settings. The content encompasses topics such as biological databases, sequence analysis, genome assembly, RNA sequence data analysis, drug design, and structural and functional analysis of proteins. In addition, it discusses computational approaches for vaccine design, systems biology and big data analysis, and machine learning in bioinformatics.It is a valuable source for bioinformaticians, computer biologists, and members of biomedical field who needs to learn bioinformatics approaches to apply to their research and lab activities. - Covers basic and more advanced developments of bioinformatics with a diverse and interdisciplinary approach to fulfill the needs of readers from different backgrounds - Explains in a practical way how to decode complex biological problems using computational approaches and resources - Brings case studies, real-world examples and several protocols to guide the readers with a problem-solving approach
Author: RASTOGI, S.C.
Publisher: PHI Learning Pvt. Ltd.
ISBN: 9354437419
Category : Science
Languages : en
Pages : 624
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Book Description
Designed as a comprehensive text for students and professionals pursuing careers in the fields of bioinformatics, molecular biology, pharmacy and drug research, the Fifth Edition continues to offer a fascinating and authoritative treatment of the entire spectrum of bioinformatics, covering a wide range of high-throughput technologies. The content can be used for four core courses: bioinformatics fundamentals, genomics, proteomics and drug discovery and design. The Fifth Edition takes a completely new pedagogical approach and the book is divided into eight distinct Units for the ease of learning: Bioinformatics Fundamentals, Sequence Alignment, Phylogenetic Analysis, Genomics, Protein Structure and Function, Drug Discovery Methods, Drug Design and Development and Integrative Topics. Accordingly, all the chapters are revised and updated in the new edition, besides introduction of seven new chapters and another seven completely re-written chapters. As a student-friendly text, it embodies several pedagogical features such as detailed examples, numerous tables, a large number of diagrams, flow charts and web resources. The book in its present edition should prove an invaluable asset to the students and researchers in the fields of bioinformatics, biotechnology, computer-aided drug design, information technology, medical diagnostics, molecular biology and pharmaceutical sciences. NEW TO THE FIFTH EDITION • Re-written chapters — Biological database search and data retrieval, Pair-wise alignment of sequences, PSSMs and Hidden Markov Models, Gene Mapping, Gene Prediction, Protein Structure Overview and Protein Structure Prediction. • Inclusion of new chapters—Scoring Matrices, Gene Sequencing, Regulatory Elements Prediction, Comparative Genomics, Protein Structure Databases, Protein Function Prediction and Potential Drug Targets. KEY FEATURES • Covers the field of bioinformatics in a complete and integrated approach – moving from the fundamentals to theory and practical applications. • State-of-the-art technologies for gene identification, molecular modeling and monitoring of cellular processes. • Data mining, data curation and analysis, classification, interpretation and efficient structure determination of genomes and proteomes. • Companion website provides useful resources for the teachers as well as for the students. So, visit Learning Centre https:// www.phindia.com/bioinformatics_mendiratta_rastogi to have access of Lecture notes, solutions manual, MCQs, problems set for practice, glossary of important terms, etc. TARGET AUDIENCE • UG and PG Students of Bioinformatics, Biotechnology, Molecular Biology and Pharmacy.
Author: Matthew He
Publisher: John Wiley & Sons
ISBN: 1118099524
Category : Computers
Languages : en
Pages : 231
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Book Description
Mathematics of Bioinformatics: Theory, Methods, and Applications provides a comprehensive format for connecting and integrating information derived from mathematical methods and applying it to the understanding of biological sequences, structures, and networks. Each chapter is divided into a number of sections based on the bioinformatics topics and related mathematical theory and methods. Each topic of the section is comprised of the following three parts: an introduction to the biological problems in bioinformatics; a presentation of relevant topics of mathematical theory and methods to the bioinformatics problems introduced in the first part; an integrative overview that draws the connections and interfaces between bioinformatics problems/issues and mathematical theory/methods/applications.
Author: S. C. Rastogi
Publisher: PHI Learning Pvt. Ltd.
ISBN: 9788120335950
Category : Bioinformatics
Languages : en
Pages : 524
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Book Description
Author: Ion Mandoiu
Publisher: John Wiley & Sons
ISBN: 0470097736
Category : Computers
Languages : en
Pages : 528
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Book Description
Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers: General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike.
Author: Xiaohua Hu
Publisher: John Wiley & Sons
ISBN: 9780470124635
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics, gene findings, drug design, RNAi and microRNA analysis, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management.
Author: Luonan Chen
Publisher: John Wiley & Sons
ISBN: 9780470488058
Category : Computers
Languages : en
Pages : 416
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Book Description
Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.
Author: Loveleen Gaur
Publisher: CRC Press
ISBN: 100046301X
Category : Technology & Engineering
Languages : en
Pages : 220
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Book Description
The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers
Author: Yi Pan
Publisher: John Wiley & Sons
ISBN: 1118345789
Category : Medical
Languages : en
Pages : 534
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Book Description
Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.
Author: Yanqing Zhang
Publisher: John Wiley & Sons
ISBN: 0470397411
Category : Computers
Languages : en
Pages : 476
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Book Description
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.
