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| bioinformatics and computational biology: Bioinformatics and Computational Biology Basant K. Tiwary, 2021-11-24 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: Bioinformatics for Systems Biology Stephen Krawetz, 2008-12-11 Bioinformatics for Systems Biology bridges and unifies many disciplines. It presents the life scientist, computational biologist, and mathematician with a common framework. Only by linking the groups together may the true life sciences revolution move forward. |
| bioinformatics and computational biology: Encyclopedia of Bioinformatics and Computational Biology Christian Schönbach, Kenta Nakai, Shoba Ranganathan, Michael Gribskov, Mario Cannataro, 2018 |
| bioinformatics and computational biology: Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology Hamid R Arabnia, Quoc Nam Tran, 2015-08-11 Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques. • Discusses the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological and behavioral systems, including applications in cancer research, computational intelligence and drug design, high-performance computing, and biology, as well as cloud and grid computing for the storage and access of big data sets. • Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with applications to general principles of DNA/RNA structure, bioinformatics and applications, genomes, protein structure, and modeling and classification, as well as microarray analysis. • Provides a systems biology perspective, including general guidelines and techniques for obtaining, integrating, and analyzing complex data sets from multiple experimental sources using computational tools and software. Topics covered include phenomics, genomics, epigenomics/epigenetics, metabolomics, cell cycle and checkpoint control, and systems biology and vaccination research. • Explains how to effectively harness the power of Big Data tools when data sets are so large and complex that it is difficult to process them using conventional database management systems or traditional data processing applications. - Discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological and behavioral systems. - Presents a systematic approach for storing, retrieving, organizing and analyzing biological data using software tools with applications. - Provides a systems biology perspective including general guidelines and techniques for obtaining, integrating and analyzing complex data sets from multiple experimental sources using computational tools and software. |
| bioinformatics and computational biology: Fundamentals of Bioinformatics and Computational Biology Gautam B. Singh, 2014-09-24 This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolboxTM. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence comparison, scoring, and determining evolutionary distance. The main focus of the third part is on modeling biological sequences and patterns as Markov chains. It presents key principles for analyzing and searching for sequences of significant motifs and biomarkers. The last part of the book, dedicated to systems biology, covers phylogenetic analysis and evolutionary tree computations, as well as gene expression analysis with microarrays. In brief, the book offers the ideal hands-on reference guide to the field of bioinformatics and computational biology. |
| bioinformatics and computational biology: Bioinformatics and Computational Biology Solutions Using R and Bioconductor Robert Gentleman, 2005-08-31 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 computational biology: Systems Biology and Bioinformatics Kayvan Najarian, Siamak Najarian, Shahriar Gharibzadeh, Christopher N. Eichelberger, 2009-04-13 The availability of molecular imaging and measurement systems enables today's biologists to swiftly monitor thousands of genes involved in a host of diseases, a critical factor in specialized drug development. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods |
| bioinformatics and computational biology: Computational Biology and Bioinformatics Ka-Chun Wong, 2016-04-27 The advances in biotechnology such as the next generation sequencing technologies are occurring at breathtaking speed. Advances and breakthroughs give competitive advantages to those who are prepared. However, the driving force behind the positive competition is not only limited to the technological advancement, but also to the companion data analy |
| bioinformatics and computational biology: Bioinformatics and Computational Biology in Drug Discovery and Development William T. Loging, 2016-03-17 A comprehensive overview of the use of computational biology approaches in the drug discovery and development process. |
| bioinformatics and computational biology: Encyclopedia of Bioinformatics and Computational Biology , 2018-08-21 Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases |
| bioinformatics and computational biology: Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology Hamid R Arabnia, Quoc Nam Tran, 2016-03-25 Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology: Systems and Applications covers the latest trends in the field with special emphasis on their applications. The first part covers the major areas of computational biology, development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques for the study of biological and behavioral systems. The second part covers bioinformatics, an interdisciplinary field concerned with methods for storing, retrieving, organizing, and analyzing biological data. The book also explores the software tools used to generate useful biological knowledge. The third part, on systems biology, explores how to obtain, integrate, and analyze complex datasets from multiple experimental sources using interdisciplinary tools and techniques, with the final section focusing on big data and the collection of datasets so large and complex that it becomes difficult to process using conventional database management systems or traditional data processing applications. - Explores all the latest advances in this fast-developing field from an applied perspective - Provides the only coherent and comprehensive treatment of the subject available - Covers the algorithm development, software design, and database applications that have been developed to foster research |
| bioinformatics and computational biology: Parallel Computing for Bioinformatics and Computational Biology Albert Y. Zomaya, 2006-04-21 Discover how to streamline complex bioinformatics applications with parallel computing This publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution. A broad range of bioinformatics applications is covered with demonstrations on how each one can be parallelized to improve performance and gain faster rates of computation. Current parallel computing techniques and technologies are examined, including distributed computing and grid computing. Readers are provided with a mixture of algorithms, experiments, and simulations that provide not only qualitative but also quantitative insights into the dynamic field of bioinformatics. Parallel Computing for Bioinformatics and Computational Biology is a contributed work that serves as a repository of case studies, collectively demonstrating how parallel computing streamlines difficult problems in bioinformatics and produces better results. Each of the chapters is authored by an established expert in the field and carefully edited to ensure a consistent approach and high standard throughout the publication. The work is organized into five parts: * Algorithms and models * Sequence analysis and microarrays * Phylogenetics * Protein folding * Platforms and enabling technologies Researchers, educators, and students in the field of bioinformatics will discover how high-performance computing can enable them to handle more complex data sets, gain deeper insights, and make new discoveries. |
| bioinformatics and computational biology: Systemic Approaches in Bioinformatics and Computational Systems Biology Paola Lecca, Dan Tulpan, Kanagasabai Rajaraman, 2012 This book presents new techniques that have resulted from the application of computer science methods to the organization and interpretation of biological data, covering three subject areas: bioinformatics, computational biology, and computational systems biology-- |
| bioinformatics and computational biology: Bioinformatics and Systems Biology Frederick Marcus, 2008-07-31 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 and computational biology: Bioinformatics Algorithms Phillip Compeau, Pavel Pevzner, 1986-06 Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of biology and computer science students alike.Each chapter begins with a central biological question, such as Are There Fragile Regions in the Human Genome? or Which DNA Patterns Play the Role of Molecular Clocks? and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides. |
| bioinformatics and computational biology: Computational Methods For Understanding Bacterial And Archaeal Genomes Ying Xu, Johann Peter Gogarten, 2008-08-06 Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative view of bacterial and archaeal genomes, and how information is encoded differently in them, is also presented. Combining theoretical discussions and computational techniques, the book serves as a valuable introductory textbook for graduate-level microbial genomics and informatics courses./a |
| bioinformatics and computational biology: Introduction to Computational Biology Michael S. Waterman, 2018-05-02 Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology. |
| bioinformatics and computational biology: Bioinformatics and Computational Biology Solutions Using R and Bioconductor Robert Gentleman, Vincent Carey, Wolfgang Huber, Rafael Irizarry, Sandrine Dudoit, 2005-12-29 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 computational biology: Dictionary of Bioinformatics and Computational Biology John M. Hancock, Marketa J. Zvelebil, 2006 |
| bioinformatics and computational biology: Applications Of Fuzzy Logic In Bioinformatics Dong Xu, James M Keller, Rajkumar Bondugula, Mihail Popescu, 2008-08-11 Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques./a |
| bioinformatics and computational biology: Problem Solving Handbook in Computational Biology and Bioinformatics Lenwood S. Heath, Naren Ramakrishnan, 2014-08-15 Bioinformatics is growing by leaps and bounds; theories/algorithms/statistical techniques are constantly evolving. Nevertheless, a core body of algorithmic ideas have emerged and researchers are beginning to adopt a problem solving approach to bioinformatics, wherein they use solutions to well-abstracted problems as building blocks to solve larger scope problems. Problem Solving Handbook for Computational Biology and Bioinformatics is an edited volume contributed by world renowned leaders in this field. This comprehensive handbook with problem solving emphasis, covers all relevant areas of computational biology and bioinformatics. Web resources and related themes are highlighted at every opportunity in this central easy-to-read reference. Designed for advanced-level students, researchers and professors in computer science and bioengineering as a reference or secondary text, this handbook is also suitable for professionals working in this industry. |
| bioinformatics and computational biology: Practical Applications of Computational Biology and Bioinformatics, 13th International Conference Florentino Fdez-Riverola, Miguel Rocha, Mohd Saberi Mohamad, Nazar Zaki, José A. Castellanos-Garzón, 2019-06-21 This book features 21 papers spanning many different sub-fields in bioinformatics and computational biology, presenting the latest research on the practical applications to promote fruitful interactions between young researchers in different areas related to the field. Next-generation sequencing technologies, together with other emerging and diverse experimental techniques, are evolving rapidly, creating numerous types of omics data. These, in turn, are creating new challenges for the expanding fields of bioinformatics and computational biology, which seek to analyse, process, integrate and extract meaningful knowledge from such data. This calls for new algorithms and approaches from fields such as databases, statistics, data mining, machine learning, optimization, computer science, machine learning and artificial intelligence. Clearly, biology is increasingly becoming a science of information, requiring tools from the computational sciences. To address these challenges, we have seen the emergence of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific areas is, more than ever, vital to boost the research efforts in the field and contribute to the training of the new generation of interdisciplinary scientists. |
| bioinformatics and computational biology: Practical Applications of Computational Biology and Bioinformatics, 12th International Conference Florentino Fdez-Riverola, Mohd Saberi Mohamad, Miguel Rocha, Juan F. De Paz, Pascual González, 2018-08-16 This book introduces the latest international research in the fields of bioinformatics and computational biology. It includes various studies in the area of machine learning in bioinformatics, systems biology, omics data analysis and mining, biomedical applications and sequences, which were selected by an international committee and presented at the 12th International Conference on Practical Applications of Computational Biology & Bioinformatics held in Toledo in June 2018. |
| bioinformatics and computational biology: Bioinformatics and Computational Biology Hamid R. Arabnia, Fernando G. Tinetti, Quoc-Nam Tran, 2020-03-13 Proceedings of the 2019 International Conference on Bioinformatics & Computational Biology (BIOCOMP'19) held July 29th - August 1st, 2019 in Las Vegas, Nevada. |
| bioinformatics and computational biology: 7th International Conference on Practical Applications of Computational Biology & Bioinformatics Mohd Saberi Mohamad, Loris Nanni, Miguel P. Rocha, Florentino Fdez-Riverola, 2013-04-19 The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘13 hopes to contribute to this effort promoting this fruitful interaction. PACBB'13 technical program included 19 papers from a submission pool of 32 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly have promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work that is being developed by each of the participants. |
| bioinformatics and computational biology: Bioinformatics Law Jorge L. Contreras, A. Jamie Cuticchia, 2013 Databases containing the accumulated genomic data of the research community are growing exponentially. This book contains cutting-edge insights from scholars, bioethicists and legal practitioners who work at the ever-changing intersection of law and bioinformatics--Page 4 of cover. |
| bioinformatics and computational biology: Basics of Bioinformatics Rui Jiang, Xuegong Zhang, Michael Q. Zhang, 2013-11-26 This book outlines 11 courses and 15 research topics in bioinformatics, based on curriculums and talks in a graduate summer school on bioinformatics that was held in Tsinghua University. The courses include: Basics for Bioinformatics, Basic Statistics for Bioinformatics, Topics in Computational Genomics, Statistical Methods in Bioinformatics, Algorithms in Computational Biology, Multivariate Statistical Methods in Bioinformatics Research, Association Analysis for Human Diseases: Methods and Examples, Data Mining and Knowledge Discovery Methods with Case Examples, Applied Bioinformatics Tools, Foundations for the Study of Structure and Function of Proteins, Computational Systems Biology Approaches for Deciphering Traditional Chinese Medicine, and Advanced Topics in Bioinformatics and Computational Biology. This book can serve as not only a primer for beginners in bioinformatics, but also a highly summarized yet systematic reference book for researchers in this field. Rui Jiang and Xuegong Zhang are both professors at the Department of Automation, Tsinghua University, China. Professor Michael Q. Zhang works at the Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. |
| bioinformatics and computational biology: Bioinformatics for Biologists Pavel Pevzner, Ron Shamir, 2011-09-15 The computational education of biologists is changing to prepare students for facing the complex datasets of today's life science research. In this concise textbook, the authors' fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors - each a leading scientist - engage the students' problem-solving skills, preparing them to meet the computational challenges of their life science careers. |
| bioinformatics and computational biology: 5th International Conference on Practical Applications of Computational Biology & Bioinformatics Miguel P. Rocha, Juan Manuel Corchado Rodríguez, Florentino Fdez Riverola, Alfonso Valencia, 2011-03-09 The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘11 hopes to contribute to this effort promoting this fruitful interaction. PACBB'11 technical program included 50 papers from a submission pool of 78 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly have promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work that is being developed by each of the participants. |
| bioinformatics and computational biology: 11th International Conference on Practical Applications of Computational Biology & Bioinformatics Florentino Fdez-Riverola, Mohd Saberi Mohamad, Miguel Rocha, Juan F. De Paz, Tiago Pinto, 2017-06-19 Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance in boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. The PACBB’17 conference was intended to contribute to this effort and promote this fruitful interaction, with a technical program that included 39 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Further, the conference promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). |
| bioinformatics and computational biology: Bioinformatics Stanley I. Letovsky, 2013-04-10 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 and computational biology: Gene-environment Interaction Analysis Sumiko Anno, 2016 This is the first book dealing with the theme of gene-environment (G×E) interaction analysis. G×E interaction analysis is a statistical method for clarifying G×E interactions applicable to a phenotype or a disease that is the result of interactions between genes and the environment. The book compiles and details cutting-edge research in bioinformatics and computational biology. Edited by Sumiko Anno, this book will appeal to anyone involved in bioinformatics and computational biology. |
| bioinformatics and computational biology: 6th International Conference on Practical Applications of Computational Biology & Bioinformatics Miguel P. Rocha, Nicholas Luscombe, Florentino Fdez-Riverola, Juan M. Corchado Rodríguez, 2012-03-05 The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘12 hopes to contribute to this effort promoting this fruitful interaction. PACBB'12 technical program included 32 papers from a submission pool of 61 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly have promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work that is being developed by each of the participants. |
| bioinformatics and computational biology: 10th International Conference on Practical Applications of Computational Biology & Bioinformatics Mohd Saberi Mohamad, Miguel P. Rocha, Florentino Fdez-Riverola, Francisco J. Domínguez Mayo, Juan F. De Paz, 2016-05-31 Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘16 hopes to contribute to this effort promoting this fruitful interaction. PACBB'16 technical program included 21 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly promote the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work being developed by each of the participants. |
| bioinformatics and computational biology: Bioinformatics Jeremy Ramsden, 2009-04-29 The field of bioinformatics continues to develop energetically. This second edition covers new findings using the formula of the original text. It is self-contained, bringing together the multiple disciplines necessary for a profound grasp of the field. |
| bioinformatics and computational biology: Advances in Computers Marvin Zelkowitz, Chau-wen Tseng, 2006-12-11 The field of bioinformatics and computational biology arose due to the need to apply techniques from computer science, statistics, informatics, and applied mathematics to solve biological problems. Scientists have been trying to study biology at a molecular level using techniques derived from biochemistry, biophysics, and genetics. Progress has greatly accelerated with the discovery of fast and inexpensive automated DNA sequencing techniques. As the genomes of more and more organisms are sequenced and assembled, scientists are discovering many useful facts by tracing the evolution of organisms by measuring changes in their DNA, rather than through physical characteristics alone. This has led to rapid growth in the related fields of phylogenetics, the study of evolutionary relatedness among various groups of organisms, and comparative genomics, the study of the correspondence between genes and other genomic features in different organisms. Comparing the genomes of organisms has allowed researchers to better understand the features and functions of DNA in individual organisms, as well as provide insights into how organisms evolve over time. The first four chapters of Advances in Computers focus on algorithms for comparing the genomes of different organisms. Possible concrete applications include identifying the basis for genetic diseases and tracking the development and spread of different forms of Avian flu. As researchers begin to better understand the function of DNA, attention has begun shifting towards the actual proteins produced by DNA. The final two chapters explore proteomic techniques for analyzing proteins directly to identify their presence and understand their physical structure. - Written by active PhD researchers in computational biology and bioinformatics |
Bioinformatics vs. Computational Biology: A Comparison
Sep 17, 2024 · While computational biology emphasizes the development of theoretical methods, computational simulations, and mathematical modeling, bioinformatics emphasizes informatics …
Bioinformatics and Computational Biology | University of ...
The mission of the Bioinformatics and Computational Biology (BICB) graduate program is to provide interdisciplinary education in the area of biomedical informatics and computational …
Journal of Bioinformatics and Computational Biology
JBCB focuses on computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact.
Computational Biology vs. Bioinformatics: What’s the Difference?
May 28, 2021 · Here are some of the main differences between computational biology and bioinformatics and when scientists should turn to each for their analyses. What is …
BS in Bioinformatics and Computational Biology - Department ...
Students integrate coursework in applied mathematics, computer science and the biological sciences, learning how to apply mathematics and computing to the study of genes and …
Bioinformatics vs. Computational Biology: Key Differences ...
Bioinformatics and computational biology leverage image processing techniques to analyze microscopy images, protein localization, and molecular interactions. Computer vision and AI …
Computational Biology vs Bioinformatics and Their Integration ...
Feb 2, 2024 · In current times of biological sciences, two fields stand out prominently: computational biology vs bioinformatics. These disciplines intersect and complement each …
Bioinformatics vs. Computational Biology: A Comparison
Sep 17, 2024 · While computational biology emphasizes the development of theoretical methods, computational simulations, and mathematical modeling, bioinformatics emphasizes informatics …
Bioinformatics and Computational Biology | University of ...
The mission of the Bioinformatics and Computational Biology (BICB) graduate program is to provide interdisciplinary education in the area of biomedical informatics and computational …
Journal of Bioinformatics and Computational Biology
JBCB focuses on computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact.
Computational Biology vs. Bioinformatics: What’s the Difference?
May 28, 2021 · Here are some of the main differences between computational biology and bioinformatics and when scientists should turn to each for their analyses. What is …
BS in Bioinformatics and Computational Biology - Department ...
Students integrate coursework in applied mathematics, computer science and the biological sciences, learning how to apply mathematics and computing to the study of genes and …
Bioinformatics vs. Computational Biology: Key Differences ...
Bioinformatics and computational biology leverage image processing techniques to analyze microscopy images, protein localization, and molecular interactions. Computer vision and AI …
Computational Biology vs Bioinformatics and Their Integration ...
Feb 2, 2024 · In current times of biological sciences, two fields stand out prominently: computational biology vs bioinformatics. These disciplines intersect and complement each …
