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| introduction to computational biology waterman: 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. |
| introduction to computational biology waterman: 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. |
| introduction to computational biology waterman: 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. |
| introduction to computational biology waterman: Dynamics of Biological Systems Michael Small, 2011-08-25 From the spontaneous rapid firing of cortical neurons to the spatial diffusion of disease epidemics, biological systems exhibit rich dynamic behaviour over a vast range of time and space scales. Unifying many of these diverse phenomena, Dynamics of Biological Systems provides the computational and mathematical platform from which to understand the underlying processes of the phenomena. Through an extensive tour of various biological systems, the text introduces computational methods for simulating spatial diffusion processes in excitable media, such as the human heart, as well as mathematical tools for dealing with systems of nonlinear ordinary and partial differential equations, such as neuronal activation and disease diffusion. The mathematical models and computer simulations offer insight into the dynamics of temporal and spatial biological systems, including cardiac pacemakers, artificial electrical defibrillation, pandemics, pattern formation, flocking behaviour, the interaction of autonomous agents, and hierarchical and structured network topologies. Tools from complex systems and complex networks are also presented for dealing with real phenomenological systems. With exercises and projects in each chapter, this classroom-tested text shows students how to apply a variety of mathematical and computational techniques to model and analyze the temporal and spatial phenomena of biological systems. MATLAB® implementations of algorithms and case studies are available on the author’s website. |
| introduction to computational biology waterman: Introduction to Computational Molecular Biology João Carlos Setubal, João Meidanis, 1997 Basic concepts of molecular biology. Strings, graphs, and algorithms. Sequence comparasion and database search. Fragment assembly of DNA. Physical mapping of DNA. Phylogenetic trees. Genome rearrangements. Molecular structure prediction. epilogue: computing with DNA. Answers to selected exercises. References. index. |
| introduction to computational biology waterman: 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. |
| introduction to computational biology waterman: Biological Sequence Analysis Richard Durbin, 1998-04-23 Presents up-to-date computer methods for analysing DNA, RNA and protein sequences. |
| introduction to computational biology waterman: Mathl Methods for DNA Sequences Michael Waterman, 1989 |
| introduction to computational biology waterman: Frontiers in Computational and Systems Biology Jianfeng Feng, Wenjiang Fu, Fengzhu Sun, 2010-06-14 Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician’s fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual’s susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially lead to the development of useful brain–machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations. |
| introduction to computational biology waterman: Introduction to Computational Biology Michael S. Waterman, Ting Chen, Fengzhu Sun, 2012-06 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. |
| introduction to computational biology waterman: Algorithms on Strings, Trees, and Sequences Dan Gusfield, 1997-05-28 String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. Its discussion of current algorithms and techniques also makes it a reference for professionals. |
| introduction to computational biology waterman: 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. |
| introduction to computational biology waterman: Advances in Bioinformatics and Computational Biology João C. Setubal, Waldeyr Mendes Silva, 2020-12-19 This book constitutes the refereed proceedings of the Brazilian Symposium on Bioinformatics, BSB 2020, held in São Paulo, Brazil, in November 2020. Due to COVID-19 pandemic the conference was held virtually The 20 revised full papers and 5 short papers were carefully reviewed and selected from 45 submissions. The papers address a broad range of current topics in computational biology and bioinformatics. |
| introduction to computational biology waterman: Handbook of Computational Molecular Biology Srinivas Aluru, 2005-12-21 The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology of |
| introduction to computational biology waterman: Bioinformatics and Phylogenetics Tandy Warnow, 2019-04-08 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. |
| introduction to computational biology waterman: Practical Computing for Biologists Steven H.D. Haddock, Casey W. Dunn, 2011-04-22 Practical Computing for Biologists shows you how to use many freely available computing tools to work more powerfully and effectively. The book was born out of the authors' own experience in developing tools for their research and helping other biologists with their computational problems. Many of the techniques are relevant to molecular bioinformatics but the scope of the book is much broader, covering topics and techniques that are applicable to a range of scientific endeavours. Twenty-two chapters organized into six parts address the following topics (and more; see Contents): • Searching with regular expressions • The Unix command line • Python programming and debugging • Creating and editing graphics • Databases • Performing analyses on remote servers • Working with electronics While the main narrative focuses on Mac OS X, most of the concepts and examples apply to any operating system. Where there are differences for Windows and Linux users, parallel instructions are provided in the margin and in an appendix. The book is designed to be used as a self-guided resource for researchers, a companion book in a course, or as a primary textbook. Practical Computing for Biologists will free you from the most frustrating and time-consuming aspects of data processing so you can focus on the pleasures of scientific inquiry. |
| introduction to computational biology waterman: Calculating the Secrets of Life National Research Council, Division on Engineering and Physical Sciences, Commission on Physical Sciences, Mathematics, and Applications, Committee on the Mathematical Sciences in Genome and Protein Structure Research, 1995-04-06 As researchers have pursued biology's secrets to the molecular level, mathematical and computer sciences have played an increasingly important roleâ€in genome mapping, population genetics, and even the controversial search for Eve, hypothetical mother of the human race. In this first-ever survey of the partnership between the two fields, leading experts look at how mathematical research and methods have made possible important discoveries in biology. The volume explores how differential geometry, topology, and differential mechanics have allowed researchers to wind and unwind DNA's double helix to understand the phenomenon of supercoiling. It explains how mathematical tools are revealing the workings of enzymes and proteins. And it describes how mathematicians are detecting echoes from the origin of life by applying stochastic and statistical theory to the study of DNA sequences. This informative and motivational book will be of interest to researchers, research administrators, and educators and students in mathematics, computer sciences, and biology. |
| introduction to computational biology waterman: Fourier Descriptors and Their Applications in Biology Pete E. Lestrel, 1997-05-13 This book discusses the theory and the practice of using Fourier descriptors as a method for measuring the shape of whole, or parts of organisms. |
| introduction to computational biology waterman: Bioinformatics Computing Bryan P. Bergeron, 2003 Comprehensive and concise, this handbook has chapters on computing visualization, large database designs, advanced pattern matching and other key bioinformatics techniques. It is a practical guide to computing in the growing field of Bioinformatics--the study of how information is represented and transmitted in biological systems, starting at the molecular level. |
| introduction to computational biology waterman: Organization of Insect Societies Jürgen Gadau, Jennifer Fewell, 2009-02-28 In this landmark volume, an international group of scientists has synthesized their collective expertise and insight into a newly unified vision of insect societies and what they can reveal about how sociality has arisen as an evolutionary strategy. Jürgen Gadau and Jennifer Fewell have assembled leading researchers from the fields of molecular biology, evolutionary genetics, neurophysiology, behavioral ecology, and evolutionary theory to reexamine the question of sociality in insects. Recent advances in social complexity theory and the sequencing of the honeybee genome ensure that this book will be valued by anyone working on sociality in insects. At the same time, the theoretical ideas presented will be of broad-ranging significance to those interested in social evolution and complex systems. |
| introduction to computational biology waterman: Algorithms in Computational Molecular Biology Mourad Elloumi, Albert Y. Zomaya, 2011-04-04 This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study. |
| introduction to computational biology waterman: BLAST Ian Korf, Mark Yandell, Joseph Bedell, 2003-07-29 This is the only book completely devoted to the popular BLAST (Basic Local Alignment Search Tool), and one that every biologist with an interest in sequence analysis should learn from. |
| introduction to computational biology waterman: Introduction to Bioinformatics Arthur M. Lesk, 2023 A vast amount of biological information about a wide range of species has become available in recent years as technological advances have significantly reduced the time it takes to sequence a genome or determine a novel protein structure. This text describes how bioinformatics can be used as a powerful set of tools for retrieving and analysing this biological data, and how bioinformatics can be applied to a wide range of disciplines such as molecular biology, medicine, biotechnology, forensic science, and anthropology. |
| introduction to computational biology waterman: The Practical Bioinformatician Limsoon Wong, 2004 Computer scientists have increasingly been enlisted as bioinformaticians to assist molecular biologists in their research. This book is a practical introduction to bioinformatics for these computer scientists. The chapters are in-depth discussions by expert bioinformaticians on both general techniques and specific approaches to a range of selected bioinformatics problems. The book is organized into clusters of chapters on the following topics: - Overview of modern molecular biology and a broad spectrum of techniques from computer science -- data mining, machine learning, mathematical modeling, sequence alignment, data integration, workflow development, etc. - In-depth discussion of computational recognition of functional and regulatory sites in DNA sequences. - Incisive discussion of computational prediction of secondary structure of RNA sequences. - Overview of computational prediction of protein cellular localization, and selected discussions of inference of protein function. - Overview of methods for discovering protein-protein interactions. - Detailed discussion of approaches to gene expression analysis for the diagnosis of diseases, the treatment of diseases, and the understanding of gene functions. - Case studies on analysis of phylogenies, functional annotation of proteins, construction of purposebuilt integrated biological databases, and development of workflows underlying the large-scale-effort gene discovery. - Written in a practical, in-depth tutorial style - Covers a broad range of bioinformatics topics and of techniques used in bioinformatics - Comprehensive overviews of the development of various approaches in a number of selectedtopics - In-depth exposition of a number of important topics - Contributions by prominent researchers: Vladimir Bajic, Ming Li, Kenta Nakai, Limsoon Wong, Cathy Wu, etc. - Extensive, integrated references to background liter |
| introduction to computational biology waterman: 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. |
| introduction to computational biology waterman: Statistical Analysis of Gene Expression Microarray Data Terry Speed, 2003-03-26 Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies |
| introduction to computational biology waterman: Handbook of Neuroevolution Through Erlang Gene I. Sher, 2012-11-06 Handbook of Neuroevolution Through Erlang presents both the theory behind, and the methodology of, developing a neuroevolutionary-based computational intelligence system using Erlang. With a foreword written by Joe Armstrong, this handbook offers an extensive tutorial for creating a state of the art Topology and Weight Evolving Artificial Neural Network (TWEANN) platform. In a step-by-step format, the reader is guided from a single simulated neuron to a complete system. By following these steps, the reader will be able to use novel technology to build a TWEANN system, which can be applied to Artificial Life simulation, and Forex trading. Because of Erlang’s architecture, it perfectly matches that of evolutionary and neurocomptational systems. As a programming language, it is a concurrent, message passing paradigm which allows the developers to make full use of the multi-core & multi-cpu systems. Handbook of Neuroevolution Through Erlang explains how to leverage Erlang’s features in the field of machine learning, and the system’s real world applications, ranging from algorithmic financial trading to artificial life and robotics. |
| introduction to computational biology waterman: 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. |
| introduction to computational biology waterman: Basic Applied Bioinformatics Chandra Sekhar Mukhopadhyay, Ratan Kumar Choudhary, Mir Asif Iquebal, 2017-09-15 An accessible guide that introduces students in all areas of life sciences to bioinformatics Basic Applied Bioinformatics provides a practical guidance in bioinformatics and helps students to optimize parameters for data analysis and then to draw accurate conclusions from the results. In addition to parameter optimization, the text will also familiarize students with relevant terminology. Basic Applied Bioinformatics is written as an accessible guide for graduate students studying bioinformatics, biotechnology, and other related sub-disciplines of the life sciences. This accessible text outlines the basics of bioinformatics, including pertinent information such as downloading molecular sequences (nucleotide and protein) from databases; BLAST analyses; primer designing and its quality checking, multiple sequence alignment (global and local using freely available software); phylogenetic tree construction (using UPGMA, NJ, MP, ME, FM algorithm and MEGA7 suite), prediction of protein structures and genome annotation, RNASeq data analyses and identification of differentially expressed genes and similar advanced bioinformatics analyses. The authors Chandra Sekhar Mukhopadhyay, Ratan Kumar Choudhary, and Mir Asif Iquebal are noted experts in the field and have come together to provide an updated information on bioinformatics. Salient features of this book includes: Accessible and updated information on bioinformatics tools A practical step-by-step approach to molecular-data analyses Information pertinent to study a variety of disciplines including biotechnology, zoology, bioinformatics and other related fields Worked examples, glossary terms, problems and solutions Basic Applied Bioinformatics gives students studying bioinformatics, agricultural biotechnology, animal biotechnology, medical biotechnology, microbial biotechnology, and zoology an updated introduction to the growing field of bioinformatics. |
| introduction to computational biology waterman: Computational Biology Röbbe Wünschiers, 2012-12-06 -Teaches the reader how to use Unix, which is the key to basic computing and allows the most flexibility for bioinformatics applications -Written specifically with the needs of molecular biologists in mind -Easy to follow, written for beginners with no computational knowledge -Includes examples from biological data analysis -Can be use either for self-teaching or in courses |
| introduction to computational biology waterman: Understanding Bioinformatics Marketa J. Zvelebil, Jeremy O. Baum, 2008 Suitable for advanced undergraduates & postgraduates, this book provides a definitive guide to bioinformatics. It takes a conceptual approach & guides the reader from first principles through to an understanding of the computational techniques & the key algorithms. |
| introduction to computational biology waterman: Bioinformatics and Molecular Evolution Paul G. Higgs, Teresa K. Attwood, 2005 In the current era of complete genome sequencing, Bioinformatics and Molecular Evolution provides an up-to-date and comprehensive introduction to bioinformatics in the context of evolutionary biology. This accessible text: provides a thorough examination of sequence analysis, biological databases, pattern recognition, and applications to genomics, microarrays, and proteomics emphasizes the theoretical and statistical methods used in bioinformatics programs in a way that is accessible to biological science students places bioinformatics in the context of evolutionary biology, including population genetics, molecular evolution, molecular phylogenetics, and their applications features end-of-chapter problems and self-tests to help students synthesize the materials and apply their understanding is accompanied by a dedicated website - www.blackwellpublishing.com/higgs - containing downloadable sequences, links to web resources, answers to self-test questions, and all artwork in downloadable format (artwork also available to instructors on CD-ROM). This important textbook will equip readers with a thorough understanding of the quantitative methods used in the analysis of molecular evolution, and will be essential reading for advanced undergraduates, graduates, and researchers in molecular biology, genetics, genomics, computational biology, and bioinformatics courses. |
| introduction to computational biology waterman: Fundamental Concepts of Bioinformatics Dan E. Krane, Michael L. Raymer, 2003 Co-authored by a biologist and computer scientist, this book is designed to make bioinformatics useful to undergraduates and prepare them for more advanced work. It covers problems at the end of each chapter, which use real data to help students apply what they have learned from both a statistical and biological point of view. |
| introduction to computational biology waterman: The Ten Most Wanted Solutions in Protein Bioinformatics Anna Tramontano, 2005-05-24 Utilizing high speed computational methods to extrapolate to the rest of the protein universe, the knowledge accumulated on a subset of examples, protein bioinformatics seeks to accomplish what was impossible before its invention, namely the assignment of functions or functional hypotheses for all known proteins.The Ten Most Wanted Solutions in Pro |
| introduction to computational biology waterman: Bioinformatics Research and Applications Ion Măndoiu, Alexander Zelikovsky, 2007-04-26 This book constitutes the refereed proceedings of the Third International Symposium on Bioinformatics Research and Applications, ISBRA 2007, held in Atlanta, GA, USA in May 2007. The 55 revised full papers presented together with three invited talks cover a wide range of topics, including clustering and classification, gene expression analysis, gene networks, genome analysis, motif finding, pathways, protein structure prediction, protein domain interactions, phylogenetics, and software tools. |
| introduction to computational biology waterman: Concepts in Bioinformatics and Genomics Jamil Momand, Alison McCurdy, 2017 Concepts in Bioinformatics and Genomics takes a conceptual approach, balancing biology, mathematics, and programming while highlighting relevant real-world applications and providing students with the tools to compute and analyze biological data. Through many thought-provoking exercises,students will develop a deeper understanding of the molecular biology, basic probability, software programs, and program-coding methodology underpinning this exciting field. |
| introduction to computational biology waterman: An Introduction to Bioinformatics Algorithms Neil C. Jones, Pavel A. Pevzner, 2004-08-06 An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website. |
| introduction to computational biology waterman: Computational Molecular Biology Peter Clote, Rolf Backofen, 2000-10-03 Recently molecular biology has undergone unprecedented developmentgenerating vast quantities of data needing sophisticatedcomputational methods for analysis, processing and archiving. Thisrequirement has given birth to the truly interdisciplinary field ofcomputational biology, or bioinformatics, a subject reliant on boththeoretical and practical contributions from statistics,mathematics, computer science and biology. * Provides the background mathematics required to understand whycertain algorithms work * Guides the reader through probability theory, entropy andcombinatorial optimization * In-depth coverage of molecular biology and protein structureprediction * Includes several less familiar algorithms such as DNAsegmentation, quartet puzzling and DNA strand separationprediction * Includes class tested exercises useful for self-study * Source code of programs available on a Web site Primarily aimed at advanced undergraduate and graduate studentsfrom bioinformatics, computer science, statistics, mathematics andthe biological sciences, this text will also interest researchersfrom these fields. |
| introduction to computational biology waterman: Algorithms in Bioinformatics Gary Benson, Roderic Page, 2003-12-08 This book constitutes the refereed proceedings of the Third International Workshop on Algorithms in Bioinformatics, WABI 2003, held in Budapest, Hungary, in September 2003. The 36 revised full papers presented were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections on comparative genomics, database searching, gene finding and expression, genome mapping, pattern and motif discovery, phylogenetic analysis, polymorphism, protein structure, sequence alignment, and string algorithms. |
| introduction to computational biology waterman: Bioinformatics for Beginners Supratim Choudhuri, 2018-10-30 Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options. |
INTRODUCTION Definition & Meaning - Merriam-Webster
The meaning of INTRODUCTION is something that introduces. How to use introduction in a sentence.
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INTRODUCTION | English meaning - Cambridge Dictionary
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What Is an Introduction? Definition & 25+ Examples - Enlightio
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Introduction - definition of introduction by The Free Dictionary
Something spoken, written, or otherwise presented in beginning or introducing something, especially: a. A preface, as to a book. b. Music A short preliminary passage in a larger …
INTRODUCTION Definition & Meaning - Merriam-Webster
The meaning of INTRODUCTION is something that introduces. How to use introduction in a sentence.
How to Write an Introduction, With Examples | Grammarly
Oct 20, 2022 · An introduction should include three things: a hook to interest the reader, some background on the topic …
INTRODUCTION | English meaning - Cambridge Dictionary
INTRODUCTION definition: 1. an occasion when something is put into use or brought to a place for the first time: 2. the act…. …
What Is an Introduction? Definition & 25+ Examples - Enl…
Nov 5, 2023 · An introduction is the initial section of a piece of writing, speech, or presentation wherein the author …
Introduction - definition of introduction by The Free Dicti…
Something spoken, written, or otherwise presented in beginning or introducing something, especially: a. A preface, as …
