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Biogeography-Based Optimization: Algorithms and Applications

by Yujun Zheng Xueqin Lu Minxia Zhang Shengyong Chen

This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors’ recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.

Bioimage Data Analysis Workflows (Learning Materials in Biosciences)

by Kota Miura Nataša Sladoje

This Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows. The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images.

Bioinformatic and Statistical Analysis of Microbiome Data: From Raw Sequences to Advanced Modeling with QIIME 2 and R

by Jun Sun Yinglin Xia

This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow for microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter so that these new methods can be readily applied in their own research. Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.

Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins (Methods of Biochemical Analysis #43)

by Andreas D. Baxevanis B. F. Ouellette

"In this book, Andy Baxevanis and Francis Ouellette . . . have undertaken the difficult task of organizing the knowledge in this field in a logical progression and presenting it in a digestible form. And they have done an excellent job. This fine text will make a major impact on biological research and, in turn, on progress in biomedicine. We are all in their debt." —Eric Lander from the Foreword Reviews from the First Edition "...provides a broad overview of the basic tools for sequence analysis ... For biologists approaching this subject for the first time, it will be a very useful handbook to keep on the shelf after the first reading, close to the computer." —Nature Structural Biology "...should be in the personal library of any biologist who uses the Internet for the analysis of DNA and protein sequence data." —Science "...a wonderful primer designed to navigate the novice through the intricacies of in scripto analysis ... The accomplished gene searcher will also find this book a useful addition to their library ... an excellent reference to the principles of bioinformatics." —Trends in Biochemical Sciences This new edition of the highly successful Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins provides a sound foundation of basic concepts, with practical discussions and comparisons of both computational tools and databases relevant to biological research. Equipping biologists with the modern tools necessary to solve practical problems in sequence data analysis, the Second Edition covers the broad spectrum of topics in bioinformatics, ranging from Internet concepts to predictive algorithms used on sequence, structure, and expression data. With chapters written by experts in the field, this up-to-date reference thoroughly covers vital concepts and is appropriate for both the novice and the experienced practitioner. Written in clear, simple language, the book is accessible to users without an advanced mathematical or computer science background. This new edition includes: All new end-of-chapter Web resources, bibliographies, and problem sets Accompanying Web site containing the answers to the problems, as well as links to relevant Web resources New coverage of comparative genomics, large-scale genome analysis, sequence assembly, and expressed sequence tags A glossary of commonly used terms in bioinformatics and genomics Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Second Edition is essential reading for researchers, instructors, and students of all levels in molecular biology and bioinformatics, as well as for investigators involved in genomics, positional cloning, clinical research, and computational biology.

Bioinformatics: Managing Scientific Data (The Morgan Kaufmann Series in Multimedia Information and Systems)

by Terence Critchlow Zoé Lacroix

Life science data integration and interoperability is one of the most challenging problems facing bioinformatics today. In the current age of the life sciences, investigators have to interpret many types of information from a variety of sources: lab instruments, public databases, gene expression profiles, raw sequence traces, single nucleotide polymorphisms, chemical screening data, proteomic data, putative metabolic pathway models, and many others. Unfortunately, scientists are not currently able to easily identify and access this information because of the variety of semantics, interfaces, and data formats used by the underlying data sources. Bioinformatics: Managing Scientific Data tackles this challenge head-on by discussing the current approaches and variety of systems available to help bioinformaticians with this increasingly complex issue. The heart of the book lies in the collaboration efforts of eight distinct bioinformatics teams that describe their own unique approaches to data integration and interoperability. Each system receives its own chapter where the lead contributors provide precious insight into the specific problems being addressed by the system, why the particular architecture was chosen, and details on the system's strengths and weaknesses. In closing, the editors provide important criteria for evaluating these systems that bioinformatics professionals will find valuable.* Provides a clear overview of the state-of-the-art in data integration and interoperability in genomics, highlighting a variety of systems and giving insight into the strengths and weaknesses of their different approaches. * Discusses shared vocabulary, design issues, complexity of use cases, and the difficulties of transferring existing data management approaches to bioinformatics systems, which serves to connect computer and life scientists. * Written by the primary contributors of eight reputable bioinformatics systems in academia and industry including: BioKris, TAMBIS, K2, GeneExpress, P/FDM, MBM, SDSC, SRS, and DiscoveryLink.

Bioinformatics: A Practical Guide to Next Generation Sequencing Data Analysis (Chapman & Hall/CRC Computational Biology Series)

by Hamid D. Ismail

This book contains the latest material in the subject, covering next generation sequencing (NGS) applications and meeting the requirements of a complete semester course. This book digs deep into analysis, providing both concept and practice to satisfy the exact need of researchers seeking to understand and use NGS data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics. The book does not introduce the analysis pipelines in a black box, but with detailed analysis steps to provide readers with the scientific and technical backgrounds required to enable them to conduct analysis with confidence and understanding. The book is primarily designed as a companion for researchers and graduate students using sequencing data analysis but will also serve as a textbook for teachers and students in biology and bioscience.

Bioinformatics: A Practical Guide to Next Generation Sequencing Data Analysis (Chapman & Hall/CRC Computational Biology Series)

by Hamid D. Ismail

This book contains the latest material in the subject, covering next generation sequencing (NGS) applications and meeting the requirements of a complete semester course. This book digs deep into analysis, providing both concept and practice to satisfy the exact need of researchers seeking to understand and use NGS data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics. The book does not introduce the analysis pipelines in a black box, but with detailed analysis steps to provide readers with the scientific and technical backgrounds required to enable them to conduct analysis with confidence and understanding. The book is primarily designed as a companion for researchers and graduate students using sequencing data analysis but will also serve as a textbook for teachers and students in biology and bioscience.

Bioinformatics: Volume I: Data, Sequence Analysis and Evolution (Methods in Molecular Biology #452)

by Jonathan M. Keith and John Walker

In this book, leading researchers in the field of Bioinformatics provide a selection of the most useful and widely applicable methods, able to be applied as is, or with minor variations, to many specific problems. Over 80 authors from around the globe contribute to the two volumes, including many leading experts in their respective subjects. They encompass topics from across the diverse field of bioinformatics through its broad scope, combining to provide an inter-disciplinary collaboration involving biologists, biochemists, physicists, mathematicians, statisticians and computer scientists.

Bioinformatics: Volume II: Structure, Function and Applications (Methods in Molecular Biology #453)

by Jonathan M. Keith

In Bioinformatics, leading researchers provide a selection of the most useful and widely applicable methods, able to be applied as is, or with minor variations, to many specific problems. Volume II: Structure, Function and Applications contains methods pertinent to the prediction of protein and RNA structures and the analysis and classification of structures, methods for inferring the function of previously identified genomic elements, chiefly protein-coding genes, medical applications in diagnostics and drug discovery, and "meta-methods" for developers of bioinformatics algorithms. Over 80 authors from around the globe have contributed to the two volumes.

Bioinformatics: Databases and Systems

by Stanley Letovsky

Bioinformatics brings computational methods to the analysis and processing of genomic data. Bioinformatics: Databases and Systems focuses on the issues of system building and data curation that dominate the day-to-day concerns of bioinformatics practitioners. Included are chapters by many of today's leading bioinformatics practitioners, describing most of the current paradigms of system building and curation, including both their strengths and weaknesses. Biological topics covered include sequence databases, metabolic pathways, phenotypes, variety collections, gene expression atlases and neuroinformatics. Species range from bacteria to mammals to plants. Software systems and technologies covered include OPM, CORBA, SRS, KLEISLI, ACEDB, Web-based integration and laboratory workflow. Bioinformatics: Databases and Systems provides a valuable introduction for newcomers to the field, and a useful reference for veterans.

Bioinformatics

by Andrzej Polanski Marek Kimmel

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.

Bioinformatics: An Introduction (Computational Biology #21)

by Jeremy Ramsden

This comprehensive textbook presents a self-contained guide to bioinformatics, defined in its broadest sense as the application of information science to biology. Thoroughly updated and greatly expanded, this third edition now includes material on the growing array of “-omics”; covering metagenomics, toxicogenomics, glycomics, lipidomics, microbiomics and phenomics. New chapters have also been added on ecosystems management and the nervous system. Emphasis is placed on providing both a firm grounding in the core concepts and a clear overview of the complete field of bioinformatics. Features: explains the fundamentals of information science relevant to biology; covers both organismal (ontogeny and phylogeny, as well as genome structure) and molecular aspects; examines the most important practical applications of bioinformatics, providing detailed descriptions of both the experimental process and the data analysis; provides a varied selection of problems throughout the book, to stimulate further thinking.

Bioinformatics: An Introduction (Computational Biology #10)

by Jeremy Ramsden

Bioinformatics: Sequences, Structures, Phylogeny

by Asheesh Shanker

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.

Bioinformatics: Problem Solving Paradigms

by Volker Sperschneider

What is this book good for? Imagine you are a computer scientist working in the bioinformatics area. P- bably you will be a member of a highly interdisciplinary team consisting of biologists, chemists, mathematicians, computer scientists ranging from p- grammers to algorithm engineers, and eventually people from various further ?elds. A major problem within such interdisciplinary teams is always to ?nd some common language, and, for each member of some discipline, to have profound knowledge of what are the notions, basic concepts and goals of the other participating disciplines, as well as of what they can contribute to the solutionofonesownproblems. Thisdoes,ofcourse,notmeanthatacomputer scientist should do the job of the biologist. Nevertheless, a computer scientist should be able to understand what a biologist deals with. On the other hand, the biologist should not do the computer scientists job, but should know what computer science and algorithm engineering might contribute to the solution of her/his problems, and also how problems should be stated in order for the computer scientist to understand them. This book primarily aims to show the potential that algorithm engin- ring o?ers for the solution of core bioinformatics problems.

Bioinformatics Algorithms: Techniques and Applications (Wiley Series in Bioinformatics #3)

by Ion Mandoiu Alexander Zelikovsky

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.

Bioinformatics and Biomarker Discovery: "Omic" Data Analysis for Personalized Medicine

by Francisco Azuaje

This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided with the knowledge needed to assess the requirements, computational approaches and outputs in disease biomarker research. Commentaries from guest experts are also included, containing detailed discussions of methodologies and applications based on specific types of "omic" data, as well as their integration. Covers the main range of data sources currently used for biomarker discovery Covers the main range of data sources currently used for biomarker discovery Puts emphasis on concepts, design principles and methodologies that can be extended or tailored to more specific applications Offers principles and methods for assessing the bioinformatic/biostatistic limitations, strengths and challenges in biomarker discovery studies Discusses systems biology approaches and applications Includes expert chapter commentaries to further discuss relevance of techniques, summarize biological/clinical implications and provide alternative interpretations

Bioinformatics and Biomarker Discovery: "Omic" Data Analysis for Personalized Medicine

by Francisco Azuaje

This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided with the knowledge needed to assess the requirements, computational approaches and outputs in disease biomarker research. Commentaries from guest experts are also included, containing detailed discussions of methodologies and applications based on specific types of "omic" data, as well as their integration. Covers the main range of data sources currently used for biomarker discovery Covers the main range of data sources currently used for biomarker discovery Puts emphasis on concepts, design principles and methodologies that can be extended or tailored to more specific applications Offers principles and methods for assessing the bioinformatic/biostatistic limitations, strengths and challenges in biomarker discovery studies Discusses systems biology approaches and applications Includes expert chapter commentaries to further discuss relevance of techniques, summarize biological/clinical implications and provide alternative interpretations

Bioinformatics and Biomedical Engineering: 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part I (Lecture Notes in Computer Science #10208)

by Ignacio Rojas and Francisco Ortuño

This two volume set LNBI 10208 and LNBI 10209 constitutes the proceedings of the 5th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2017, held in Granada, Spain, in April 2017. The 122 papers presented were carefully reviewed and selected from 309 submissions. The scope of the conference spans the following areas: advances in computational intelligence for critical care; bioinformatics for healthcare and diseases; biomedical engineering; biomedical image analysis; biomedical signal analysis; biomedicine; challenges representing large-scale biological data; computational genomics; computational proteomics; computational systems for modeling biological processes; data driven biology - new tools, techniques and resources; eHealth; high-throughput bioinformatic tools for genomics; oncological big data and new mathematical tools; smart sensor and sensor-network architectures; time lapse experiments and multivariate biostatistics.

Bioinformatics and Biomedical Engineering: 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part II (Lecture Notes in Computer Science #10209)

by Ignacio Rojas and Francisco Ortuño

This two volume set LNBI 10208 and LNBI 10209 constitutes the proceedings of the 5th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2017, held in Granada, Spain, in April 2017. The 122 papers presented were carefully reviewed and selected from 309 submissions. The scope of the conference spans the following areas: advances in computational intelligence for critical care; bioinformatics for healthcare and diseases; biomedical engineering; biomedical image analysis; biomedical signal analysis; biomedicine; challenges representing large-scale biological data; computational genomics; computational proteomics; computational systems for modeling biological processes; data driven biology - new tools, techniques and resources; eHealth; high-throughput bioinformatic tools for genomics; oncological big data and new mathematical tools; smart sensor and sensor-network architectures; time lapse experiments and multivariate biostatistics.

Bioinformatics and Biomedical Engineering: Third International Conference, IWBBIO 2015, Granada, Spain, April 15-17, 2015. Proceedings, Part II (Lecture Notes in Computer Science #9044)

by Francisco Ortuño Ignacio Rojas

The two volume set LNCS 9043 and 9044 constitutes the refereed proceedings of the Third International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015, held in Granada, Spain, in April 2015.The 135 papers presented were carefully reviewed and selected from 268 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases, biomedical engineering, biomedical image analysis, biomedical signal analysis, computational genomics, computational proteomics, computational systems for modelling biological processes, e Health, next generation sequencing and sequence analysis, quantitative and systems pharmacology, Hidden Markov Model (HMM) for biological sequence modeling, advances in computational intelligence for bioinformatics and biomedicine, tools for next generation sequencing data analysis, dynamics networks in system medicine, interdisciplinary puzzles of measurements in biological systems, biological networks, high performance computing in bioinformatics, computational biology and computational chemistry, advances in drug discovery and ambient intelligence for bio emotional computing.

Bioinformatics and Biomedical Engineering: Third International Conference, IWBBIO 2015, Granada, Spain, April 15-17, 2015. Proceedings, Part I (Lecture Notes in Computer Science #9043)

by Francisco Ortuño Ignacio Rojas

The two volume set LNCS 9043 and 9044 constitutes the refereed proceedings of the Third International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015, held in Granada, Spain in April 2015. The 134 papers presented were carefully reviewed and selected from 268 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases, biomedical engineering, biomedical image analysis, biomedical signal analysis, computational genomics, computational proteomics, computational systems for modelling biological processes, eHealth, next generation sequencing and sequence analysis, quantitative and systems pharmacology, Hidden Markov Model (HMM) for biological sequence modeling, advances in computational intelligence for bioinformatics and biomedicine, tools for next generation sequencing data analysis, dynamics networks in system medicine, interdisciplinary puzzles of measurements in biological systems, biological networks, high performance computing in bioinformatics, computational biology and computational chemistry, advances in drug discovery and ambient intelligence for bio emotional computing.

Bioinformatics and Biomedical Engineering: 4th International Conference, IWBBIO 2016, Granada, Spain, April 20-22, 2016, Proceedings (Lecture Notes in Computer Science #9656)

by Francisco Ortuño Ignacio Rojas

This book constitutes the refereed proceedings of the 4th International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2016, held in Granada, Spain, in April 2016. The 69 papers presented were carefully reviewed and selected from 286 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; biomedical image analysis; biomedical signal analysis; computational systems for modeling biological processes; eHealth; tools for next generation sequencing data analysis; assistive technology for people with neuromotor disorders; fundamentals of biological dynamics and maximization of the information extraction from the experiments in the biological systems; high performance computing in bioinformatics, computational biology and computational chemistry; human behavior monitoring, analysis and understanding; pattern recognition and machine learning in the -omics sciences; and resources for bioinformatics.

Bioinformatics and Biomedical Engineering: 6th International Work-Conference, IWBBIO 2018, Granada, Spain, April 25–27, 2018, Proceedings, Part I (Lecture Notes in Computer Science #10813)

by Ignacio Rojas Francisco Ortuño

This two-volume set LNBI 10813 and LNBI 10814 constitutes the proceedings of the 6th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2018, held in Granada, Spain, in April 2018.The 88 regular papers presented were carefully reviewed and selected from 273 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; bioinformatics tools to integrate omics dataset and address biological question; challenges and advances in measurement and self-parametrization of complex biological systems; computational genomics; computational proteomics; computational systems for modelling biological processes; drug delivery system design aided by mathematical modelling and experiments; generation, management and biological insights from big data; high-throughput bioinformatic tools for medical genomics; next generation sequencing and sequence analysis; interpretable models in biomedicine and bioinformatics; little-big data. Reducing the complexity and facing uncertainty of highly underdetermined phenotype prediction problems; biomedical engineering; biomedical image analysis; biomedical signal analysis; challenges in smart and wearable sensor design for mobile health; and healthcare and diseases.

Bioinformatics and Biomedical Engineering: 6th International Work-Conference, IWBBIO 2018, Granada, Spain, April 25–27, 2018, Proceedings, Part II (Lecture Notes in Computer Science #10814)

by Ignacio Rojas Francisco Ortuño

This two volume set LNBI 10813 and LNBI 10814 constitutes the proceedings of the 6th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2018, held in Granada, Spain, in April 2018.The 88 regular papers presented were carefully reviewed and selected from 273 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; bioinformatics tools to integrate omics dataset and address biological question; challenges and advances in measurement and self-parametrization of complex biological systems; computational genomics; computational proteomics; computational systems for modelling biological processes; drug delivery system design aided by mathematical modelling and experiments; generation, management and biological insights from big data; high-throughput bioinformatic tools for medical genomics; next generation sequencing and sequence analysis; interpretable models in biomedicine and bioinformatics; little-big data. Reducing the complexity and facing uncertainty of highly underdetermined phenotype prediction problems; biomedical engineering; biomedical image analysis; biomedical signal analysis; challenges in smart and wearable sensor design for mobile health; and healthcare and diseases.

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Showing 11,101 through 11,125 of 85,187 results