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Bioinformatics and Computational Biology: A Primer for Biologists

This textbook introduces fundamental concepts of bioinformatics and computational biology to the students and researchers in biology, medicine, veterinary science, agriculture, and bioengineering . The respective chapters provide detailed information on biological databases, sequence alignment, molecular evolution, next-generation sequencing, systems biology, and statistical computing using R. The book also presents a case-based discussion on clinical, veterinary, agricultural bioinformatics, and computational bioengineering for application-based learning in the respective fields. Further, it offers readers guidance on reconstructing and analysing biological networks and highlights computational methods used in systems medicine and genome-wide association mapping of diseases. Given its scope, this textbook offers an essential introductory book on bioinformatics and computational biology for undergraduate and graduate students in the life sciences, botany, zoology, physiology, biotechnology, bioinformatics, and genomic science as well as systems biology, bioengineering and the agricultural, and veterinary sciences.

Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities

Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated, at an unprecedented rate, at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology, it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources, algorithms, and methods, it equips readers with the confidence to both analyze biological data and estimate predictions.The book offers comprehensive coverage of the most essential and emerging topics: Cloud-based monitoring of bioinformatics multivariate data with cloud platforms Machine learning and deep learning in bioinformatics Quantum machine learning for biological applications Integrating machine learning strategies with multiomics to augment prognosis in chronic diseases Biomedical engineering Next generation sequencing techniques and applications Computational systems biology and molecular evolution While other books may touch on some of the same issues and nuances of biological data analysis, they neglect to feature bioinformatics and computational biology exclusively, and as exhaustively. This book's abundance of several subtopics related to almost all of the regulatory activities of biomolecules from where real data is being generated brings an added dimension.

Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)

Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms

BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.

Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms

BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.

Bioinformatics and Phylogenetics: Seminal Contributions of Bernard Moret (Computational Biology #29)

This volume presents a compelling collection of state-of-the-art work in algorithmic computational biology, honoring the legacy of Professor Bernard M.E. Moret in this field. Reflecting the wide-ranging influences of Prof. Moret’s research, the coverage encompasses such areas as phylogenetic tree and network estimation, genome rearrangements, cancer phylogeny, species trees, divide-and-conquer strategies, and integer linear programming. Each self-contained chapter provides an introduction to a cutting-edge problem of particular computational and mathematical interest.Topics and features: addresses the challenges in developing accurate and efficient software for the NP-hard maximum likelihood phylogeny estimation problem; describes the inference of species trees, covering strategies to scale phylogeny estimation methods to large datasets, and the construction of taxonomic supertrees; discusses the inference of ultrametric distances from additive distance matrices, and the inference of ancestral genomes under genome rearrangement events; reviews different techniques for inferring evolutionary histories in cancer, from the use of chromosomal rearrangements to tumor phylogenetics approaches; examines problems in phylogenetic networks, including questions relating to discrete mathematics, and issues of statistical estimation; highlights how evolution can provide a framework within which to understand comparative and functional genomics; provides an introduction to Integer Linear Programming and its use in computational biology, including its use for solving the Traveling Salesman Problem.Offering an invaluable source of insights for computer scientists, applied mathematicians, and statisticians, this illuminating volume will also prove useful for graduate courses on computational biology and bioinformatics.

Bioinformatics and Systems Biology: Collaborative Research and Resources

Collaborative research in bioinformatics and systems biology is a key element of modern biology and health research. This book highlights and provides access to many of the methods, environments, results and resources involved, including integral laboratory data generation and experimentation and clinical activities. Collaborative projects embody a research paradigm that connects many of the top scientists, institutions, their resources and research worldwide, resulting in first-class contributions to bioinformatics and systems biology. Central themes include describing processes and results in collaborative research projects using computational biology and providing a guide for researchers to access them. The book is also a practical guide on how science is managed. It shows how collaborative researchers are putting results together in a way accessible to the entire biomedical community.

Bioinformatics Database Systems

Modern biological databases comprise not only data, but also sophisticated query facilities and bioinformatics data analysis tools. This book provides an exploration through the world of Bioinformatics Database Systems. The book summarizes the popular and innovative bioinformatics repositories currently available, including popular primary genetic and protein sequence databases, phylogenetic databases, structure and pathway databases, microarray databases and boutique databases. It also explores the data quality and information integration issues currently involved with managing bioinformatics databases, including data quality issues that have been observed, and efforts in the data cleaning field. Biological data integration issues are also covered in-depth, and the book demonstrates how data integration can create new repositories to address the needs of the biological communities. It also presents typical data integration architectures employed in current bioinformatics databases. The latter part of the book covers biological data mining and biological data processing approaches using cloud-based technologies. General data mining approaches are discussed, as well as specific data mining methodologies that have been successfully deployed in biological data mining applications. Two biological data mining case studies are also included to illustrate how data, query, and analysis methods are integrated into user-friendly systems. Aimed at researchers and developers of bioinformatics database systems, the book is also useful as a supplementary textbook for a one-semester upper-level undergraduate course, or an introductory graduate bioinformatics course.

Bioinformatics Database Systems

Modern biological databases comprise not only data, but also sophisticated query facilities and bioinformatics data analysis tools. This book provides an exploration through the world of Bioinformatics Database Systems. The book summarizes the popular and innovative bioinformatics repositories currently available, including popular primary genetic and protein sequence databases, phylogenetic databases, structure and pathway databases, microarray databases and boutique databases. It also explores the data quality and information integration issues currently involved with managing bioinformatics databases, including data quality issues that have been observed, and efforts in the data cleaning field. Biological data integration issues are also covered in-depth, and the book demonstrates how data integration can create new repositories to address the needs of the biological communities. It also presents typical data integration architectures employed in current bioinformatics databases. The latter part of the book covers biological data mining and biological data processing approaches using cloud-based technologies. General data mining approaches are discussed, as well as specific data mining methodologies that have been successfully deployed in biological data mining applications. Two biological data mining case studies are also included to illustrate how data, query, and analysis methods are integrated into user-friendly systems. Aimed at researchers and developers of bioinformatics database systems, the book is also useful as a supplementary textbook for a one-semester upper-level undergraduate course, or an introductory graduate bioinformatics course.

Bioinformatics for Evolutionary Biologists: A Problems Approach

This self-contained textbook covers fundamental aspects of sequence analysis in evolutionary biology, including sequence alignment, phylogeny reconstruction, and coalescent simulation. It addresses these aspects through a series of over 400 computer problems, ranging from elementary to research level to enable learning by doing. Students solve the problems in the same computational environment used for decades in science – the UNIX command line. This is available on all three major operating systems for PCs: Microsoft Windows, Mac-OSX, and Linux. To learn using this powerful system, students analyze sample sequence data by applying generic tools, bioinformatics software, and over 40 programs specifically written for this course. The solutions for all problems are included, making the book ideal for self-study. Problems are grouped into sections headed by an introduction and a list of new concepts and programs. By using practical computing to explore evolutionary concepts and sequence data, the book enables readers to tackle their own computational problems.

Bioinformatics for Oral Cancer: Current Insights and Advances

Amid the rising global concern of oral cancer, this book provides a compelling exploration of the intricate oral cavity, focused on shedding light on early diagnosis and addressing outdated paradigms, it delves into the persistent challenges of oral premalignant lesions. Tailored for both beginners and researchers, its six chapters encompass the spectrum of genome sequencing, diagnostic biomarkers, gene expression, and more. Discover a fusion of basic and clinical sciences, aiming to invigorate the study of bioinformatics and oral cancer, and ultimately improve survival rates.Bioinformatics for Oral Cancer: Current Insights and Advances serves as a comprehensive guide, offering a deep dive into the multifaceted landscape of oral cancer research and bioinformatics. Within its pages, readers will uncover a wealth of knowledge, starting with foundational chapters introducing bioinformatics and establishing the backdrop of oral cancer. The book then progresses into the realm of diagnostic biomarkers, revealing cutting-edge methodologies for their identification in the context of oral cancer. The book’s keen focus extends to gene expression profiles and the intricacies of gene sequencing in the context of oral cancer progression. By systematically unravelling these critical aspects, the book bridges the gap between basic and clinical sciences, equipping readers with a holistic understanding of bioinformatics’ pivotal role in enhancing our grasp of oral cancer’s complexities.By deciphering the enigmatic landscape of oral premalignant lesions, the book equips clinicians and researchers with tools to predict malignant potentials. Its meticulous exploration of gene expression profiles and sequencing promises to reshape early detection strategies, propelling the field towards improved diagnosis and treatment outcomes.

Bioinformatics for Oral Cancer: Current Insights and Advances

Amid the rising global concern of oral cancer, this book provides a compelling exploration of the intricate oral cavity, focused on shedding light on early diagnosis and addressing outdated paradigms, it delves into the persistent challenges of oral premalignant lesions. Tailored for both beginners and researchers, its six chapters encompass the spectrum of genome sequencing, diagnostic biomarkers, gene expression, and more. Discover a fusion of basic and clinical sciences, aiming to invigorate the study of bioinformatics and oral cancer, and ultimately improve survival rates.Bioinformatics for Oral Cancer: Current Insights and Advances serves as a comprehensive guide, offering a deep dive into the multifaceted landscape of oral cancer research and bioinformatics. Within its pages, readers will uncover a wealth of knowledge, starting with foundational chapters introducing bioinformatics and establishing the backdrop of oral cancer. The book then progresses into the realm of diagnostic biomarkers, revealing cutting-edge methodologies for their identification in the context of oral cancer. The book’s keen focus extends to gene expression profiles and the intricacies of gene sequencing in the context of oral cancer progression. By systematically unravelling these critical aspects, the book bridges the gap between basic and clinical sciences, equipping readers with a holistic understanding of bioinformatics’ pivotal role in enhancing our grasp of oral cancer’s complexities.By deciphering the enigmatic landscape of oral premalignant lesions, the book equips clinicians and researchers with tools to predict malignant potentials. Its meticulous exploration of gene expression profiles and sequencing promises to reshape early detection strategies, propelling the field towards improved diagnosis and treatment outcomes.

Bioinformatics in Aquaculture: Principles and Methods

Bioinformatics derives knowledge from computer analysis of biological data. In particular, genomic and transcriptomic datasets are processed, analysed and, whenever possible, associated with experimental results from various sources, to draw structural, organizational, and functional information relevant to biology. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics in Aquaculture provides the most up to date reviews of next generation sequencing technologies, their applications in aquaculture, and principles and methodologies for the analysis of genomic and transcriptomic large datasets using bioinformatic methods, algorithm, and databases. The book is unique in providing guidance for the best software packages suitable for various analysis, providing detailed examples of using bioinformatic software and command lines in the context of real world experiments. This book is a vital tool for all those working in genomics, molecular biology, biochemistry and genetics related to aquaculture, and computational and biological sciences.

Bioinformatics in Aquaculture: Principles and Methods

Bioinformatics derives knowledge from computer analysis of biological data. In particular, genomic and transcriptomic datasets are processed, analysed and, whenever possible, associated with experimental results from various sources, to draw structural, organizational, and functional information relevant to biology. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics in Aquaculture provides the most up to date reviews of next generation sequencing technologies, their applications in aquaculture, and principles and methodologies for the analysis of genomic and transcriptomic large datasets using bioinformatic methods, algorithm, and databases. The book is unique in providing guidance for the best software packages suitable for various analysis, providing detailed examples of using bioinformatic software and command lines in the context of real world experiments. This book is a vital tool for all those working in genomics, molecular biology, biochemistry and genetics related to aquaculture, and computational and biological sciences.

Bioinformatics in Personalized Medicine: 10th Spanish Symposium, JBI 2010, Torremolinos, Spain, October 27-29, 2010. Revised Selected Papers (Lecture Notes in Computer Science #6620)

This book constitutes the refereed proceedings of the 10th Spanish Symposium on Bioinformatics, JBI 2010, held in Torremolinos, Spain, in October 2010. The 13 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are structured in topical sections on next-generation sequencing data; genome-wide association studies; high-performanced databases; text-mining; tools for integration of Web services; ontologies; analysis and visualization of omics data.

Bioinformatics of Human Proteomics (Translational Bioinformatics #3)

“Bioinformatics of Human Proteomics” discusses the development of methods, techniques and applications in the field of protein bioinformatics, an important direction in bioinformatics. It collects contributions from expert researchers in order to provide a practical guide to this complex field of study. The book covers the protein interaction network, drug discovery and development, the relationship between translational medicine and bioinformatics, and advances in proteomic methods, while also demonstrating important bioinformatics tools and methods available today for protein analysis, interpretation and predication. It is intended for experts or senior researchers in the fields of clinical research-related biostatistics, bioinformatics, computational biology, medicine, statistics, system biology, molecular diagnostics, biomarkers, or drug discovery and development. Dr.Xiangdong Wang works as a distinguished professor of Respiratory Medicine at Fudan University, Shanghai, China. He serves as Director of Biomedical Research Center, Fudan University Zhongshan Hospital and adjunct professor of Clinical Bioinformatics at Lund University, Sweden. His main research is focused on the role of clinical bioinformatics in the development of disease-specific biomarkers and dynamic network biomarkers, the molecular mechanism of organ dysfunction and potential therapies.

Bioinformatics of Non Small Cell Lung Cancer and the Ras Proto-Oncogene (SpringerBriefs in Applied Sciences and Technology)

Cancer is initiated by activation of oncogenes or inactivation of tumor suppressor genes. Mutations in the K-ras proto-oncogene are responsible for 10–30% of adenocarcinomas. Clinical Findings point to a wide variety of other cancers contributing to lung cancer incidence. Such a scenario makes identification of lung cancer difficult and thus identifying its mechanisms can contribute to the society. Identifying unique conserved patterns common to contributing proto-oncogenes may further be a boon to Pharmacogenomics and pharmacoinformatics. This calls for ab initio/de novo drug discovery that in turn will require a comprehensive in silico approach of Sequence, Domain, Phylogenetic and Structural analysis of the receptors, ligand screening and optimization and detailed Docking studies.This brief involves extensive role of the RAS subfamily that includes a set of proteins, which cause an over expression of cancer-causing genes like M-ras and initiate tumour formation in lungs. SNP Studies and Structure based drug discovery will also be undertaken.

Bioinformatics of the Brain

The brain consisting of billions of neurons is probably the most complex and mysterious organ of the body. Understanding the functioning of the brain in its health and disease states has baffled the researchers working in this area for many years. The diversity of brain diseases and disorders makes the analysis of brain functions an even more challenging area of research. In vitro and in vivo studies regarding the brain may be laborious, however, bioinformatics using in silico approaches may take the burden off the experimental studies and give us a clearer perspective on disease and healthy states of the brain, its functions, and disease mechanisms.Recent advancements in neuroimaging technologies, the development of high-performance computers and the development of software, algorithms and methods to analyze data obtained from various neuroimaging processes have opened new frontiers in neuroscience enabling unprecedented finer analysis of the brain functions. This relatively new approach of brain analysis which may be termed Bioinformatics of the Brain is the main subject of this volume aiming to provide a thorough review of various bioinformatics approaches for analyzing the functioning of the brain and understanding brain diseases such as neurodegenerative diseases, brain tumors, and neuropsychiatric disorders. Authors from various disciplines in this volume each focus on a different aspect aiming to expand our understanding of this area of research. Topics included are: Brain diseases and disorders Stem cell therapy of neurodegenerative diseases Tissue engineering applications of gliomas Brain tumor detection and modeling Brain tumor growth simulation Brain-computer interface Bioinformatics of brain diseases Graph-theoretical analysis of complex brain networks Brain proteomics This book is intended to aid scientists, researchers, and graduate students in carrying out interdisciplinary research in the areas of bioinformatics, bioengineering, computer engineering, software engineering, mathematics, molecular biology, genetics, and biotechnology.

Bioinformatics of the Brain

The brain consisting of billions of neurons is probably the most complex and mysterious organ of the body. Understanding the functioning of the brain in its health and disease states has baffled the researchers working in this area for many years. The diversity of brain diseases and disorders makes the analysis of brain functions an even more challenging area of research. In vitro and in vivo studies regarding the brain may be laborious, however, bioinformatics using in silico approaches may take the burden off the experimental studies and give us a clearer perspective on disease and healthy states of the brain, its functions, and disease mechanisms.Recent advancements in neuroimaging technologies, the development of high-performance computers and the development of software, algorithms and methods to analyze data obtained from various neuroimaging processes have opened new frontiers in neuroscience enabling unprecedented finer analysis of the brain functions. This relatively new approach of brain analysis which may be termed Bioinformatics of the Brain is the main subject of this volume aiming to provide a thorough review of various bioinformatics approaches for analyzing the functioning of the brain and understanding brain diseases such as neurodegenerative diseases, brain tumors, and neuropsychiatric disorders. Authors from various disciplines in this volume each focus on a different aspect aiming to expand our understanding of this area of research. Topics included are: Brain diseases and disorders Stem cell therapy of neurodegenerative diseases Tissue engineering applications of gliomas Brain tumor detection and modeling Brain tumor growth simulation Brain-computer interface Bioinformatics of brain diseases Graph-theoretical analysis of complex brain networks Brain proteomics This book is intended to aid scientists, researchers, and graduate students in carrying out interdisciplinary research in the areas of bioinformatics, bioengineering, computer engineering, software engineering, mathematics, molecular biology, genetics, and biotechnology.

Bioinformatics Research and Application: 7th International Symposium, ISBRA 2011, Changsha, China, May 27-29, 2011, Proceedings (Lecture Notes in Computer Science #6674)

This volume constitutes the refereed proceedings of the 7th International Symposium on Bioinformatics Research and Applications, ISBRA 2011, held in Changsha, China, in May 2011. The 36 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 92 submissions. Topics presented span all areas of bioinformatics and computational biology, including the development of experimental or commercial systems.

Bioinformatics Research and Applications: 18th International Symposium, ISBRA 2022, Haifa, Israel, November 14–17, 2022, Proceedings (Lecture Notes in Computer Science #13760)

This book constitutes the proceedings of the 18th International Symposium on Bioinformatics Research and Applications, ISBRA 2022, held in Haifa, Israel, in November 14–17, 2022.The 30 full papers and 4 short papers presented in this book were carefully reviewed and selected from 72 submissions. They were organized in topical sections named: AI and disease; computational proteomics; biomedical imaging; drug screening and drug-drug interaction prediction; Biomedical data; sequencing data analysis.

Bioinformatics Research and Applications: 10th International Symposium, ISBRA 2014, Zhangjiajie, China, June 28-30, 2014, Proceedings (Lecture Notes in Computer Science #8492)

This book constitutes the refereed proceedings of the 10th International Symposium on Bioinformatics Research and Applications, ISBRA 2014, held in Zhangjiajie, China, in June 2014. The 33 revised full papers and 31 one-page abstracts included in this volume were carefully reviewed and selected from 119 submissions. The papers cover a wide range of topics in bioinformatics and computational biology and their applications including the development of experimental or commercial systems.

Bioinformatics Research and Applications: 6th International Symposium, ISBRA 2010, Storrs, CT, USA, May 23-26, 2010. Proceedings (Lecture Notes in Computer Science #6053)

Bioinformatics Research and Applications: 12th International Symposium, ISBRA 2016, Minsk, Belarus, June 5-8, 2016, Proceedings (Lecture Notes in Computer Science #9683)

This book constitutes the proceedings of the 12th International Symposium on Bioinformatics Research and Applications, ISBRA 2016, held in Minsk, Belarus, in June 2016. The 25 papers presented in this volume were carefully reviewed and selected from 77 submissions. They were organized in topical sections named: next generation sequencing data analysis; protein-protein interactions and networks; protein and RNA structure; phylogenetics; sequence analysis; and statistical methods.

Bioinformatics Research and Applications: 9th International Symposium, ISBRA 2013, Charlotte, NC, USA, May 20-22, 2013, Proceedings (Lecture Notes in Computer Science #7875)

This book constitutes the refereed proceedings of the 9th International Symposium on Bioinformatics Research and Applications, ISBRA 2013, held in Charlotte, NC, USA, in May 2013. The 25 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 46 submissions. The papers cover a wide range of biomedical databases and data integration, high-performance bio-computing, biomolecular imaging, high-throughput sequencing data analysis, bio-ontologies, molecular evolution, comparative genomics and phylogenomics, molecular modeling and simulation, pattern discovery and classification, computational proteomics, population genetics, data mining and visualization, software tools and applications.