Theory And Mathematical Methods For Bioinformatics 1 E
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Theory And Mathematical Methods For Bioinformatics 1 E
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Author : Shen
language : en
Publisher:
Release Date : 2010-12-01
Theory And Mathematical Methods For Bioinformatics 1 E written by Shen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-01 with categories.
This monograph addresses, in a systematic and pedagogical manner, the mathematical methods and the algorithms required to deal with the molecularly based problems of bioinformatics. The book will be useful to students, research scientists and practitioners of bioinformatics and related fields, especially those who are interested in the underlying mathematical methods and theory. Among the methods presented in the book, prominent attention is given to pair-wise and multiple sequence alignment algorithms, stochastic models of mutations, modulus structure theory and protein configuration analysis. Strong links to the molecular structures of proteins, DNA and other biomolecules and their analyses are developed. In particular, for proteins an in-depth exposition of secondary structure prediction methods should be a valuable tool in both molecular biology and in applications to rational drug design. The book can also be used as a textbook and for this reason most of the chapters include exercises and problems at the level of a graduate program in bioinformatics.
Mathematics Of Bioinformatics
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Author : Matthew He
language : en
Publisher: John Wiley & Sons
Release Date : 2011-03-16
Mathematics Of Bioinformatics written by Matthew He and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-16 with Computers categories.
Mathematics of Bioinformatics: Theory, Methods, and Applications provides a comprehensive format for connecting and integrating information derived from mathematical methods and applying it to the understanding of biological sequences, structures, and networks. Each chapter is divided into a number of sections based on the bioinformatics topics and related mathematical theory and methods. Each topic of the section is comprised of the following three parts: an introduction to the biological problems in bioinformatics; a presentation of relevant topics of mathematical theory and methods to the bioinformatics problems introduced in the first part; an integrative overview that draws the connections and interfaces between bioinformatics problems/issues and mathematical theory/methods/applications.
Theory And Mathematical Methods In Bioinformatics
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Author : Shiyi Shen
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-26
Theory And Mathematical Methods In Bioinformatics written by Shiyi Shen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-26 with Science categories.
This monograph addresses, in a systematic and pedagogical manner, the mathematical methods and the algorithms required to deal with the molecularly based problems of bioinformatics. Prominent attention is given to pair-wise and multiple sequence alignment algorithms, stochastic models of mutations, modulus structure theory and protein configuration analysis. Strong links to the molecular structures of proteins, DNA and other biomolecules and their analyses are developed.
Introduction To Mathematical Methods In Bioinformatics
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Author : Alexander Isaev
language : en
Publisher: Springer
Release Date : 2006-10-04
Introduction To Mathematical Methods In Bioinformatics written by Alexander Isaev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-04 with Science categories.
This book looks at the mathematical foundations of the models currently in use. All existing books on bioinformatics are software-orientated and they concentrate on computer implementations of mathematical models of biology. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.
Pattern Discovery In Bioinformatics
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Author : Laxmi Parida
language : en
Publisher: CRC Press
Release Date : 2007-07-04
Pattern Discovery In Bioinformatics written by Laxmi Parida and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-04 with Computers categories.
The computational methods of bioinformatics are being used more and more to process the large volume of current biological data. Promoting an understanding of the underlying biology that produces this data, Pattern Discovery in Bioinformatics: Theory and Algorithms provides the tools to study regularities in biological data. Taking a systema
Statistical Methods In Bioinformatics
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Author : Warren J. Ewens
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-09-30
Statistical Methods In Bioinformatics written by Warren J. Ewens and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09-30 with Science categories.
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)
Mathematical Principles In Bioinformatics
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Author : Stephen S.-T. Yau
language : en
Publisher: Springer
Release Date : 2024-02-01
Mathematical Principles In Bioinformatics written by Stephen S.-T. Yau and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-01 with Science categories.
This textbook introduces bioinformatics to students in mathematics with no biology background assumed and it provides solid mathematical tools for biology students along with an understanding of how to implement them in bioinformatics problems. In addition to the basics, the text offers new approaches to understanding biological sequences. The concise presentation distinguishes itself from others on the subject, discussing and providing principles that relate to current open problems in bioinformatics as well as considering a variety of models. The convex hull principle is highlighted, opening a new interdisciplinary research area at the intersection of biology, mathematics, and computer science. Prerequisites include first courses in linear algebra, probability and statistics, and mathematical analysis. Researchers in mathematics, biology, and math-biology, will also find aspects of this text useful. This textbook is written based on the authors' research works that have been published in various journals along with the lecture notes used when teaching bioinformatics courses at the University of Illinois at Chicago and at Tsinghua University. The content may be divided into two parts. The first part includes three chapters, introducing some basic concepts. Chapter 1 provides biological background in molecular biology for mathematicians. Chapter 2 describes biological databases that are commonly used. Chapter 3 is concerned with alignment methods including global/local alignment, heuristic alignment, and multiple alignment. The second part consisting of five chapters, describes several bioinformatics principles using a rigorous mathematical formulation. Chapter 4 introduces the time-frequency spectral principle and its applications in bioinformatics. In Chapters 5 and 6, two strategies are used, the graphical representation and the natural vector method, to represent biological sequences, and conduct sequence comparison and phylogenetic analysis without alignment. Chapter 7 presents the convex hull principle and shows how it can be used to mathematically determine whether a certain amino acid sequence can be a protein. The last chapter summarizes additional mathematical ideas relating to sequence comparisons, such as new feature vectors and metrics. This part focuses on the governing principle in biology and provides plenty of alignment-free methods, which cannot be found in any other book.
Statistical Methods In Bioinformatics
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Author : Warren J. Ewens
language : en
Publisher: Springer
Release Date : 2008-11-01
Statistical Methods In Bioinformatics written by Warren J. Ewens and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-01 with Science categories.
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)
Algorithms In Bioinformatics
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Author : Paul A. Gagniuc
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-10
Algorithms In Bioinformatics written by Paul A. Gagniuc and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-10 with Mathematics categories.
ALGORITHMS IN BIOINFORMATICS Explore a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields Algorithms in Bioinformatics: Theory and Implementation delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. The text incorporates graphical illustrations to highlight and emphasize the technical details of computational algorithms found within, to further the reader’s understanding and retention of the material. Throughout, the book is written in an accessible and practical manner, showing how algorithms can be implemented and used in JavaScript on Internet Browsers. The author has included more than 120 open-source implementations of the material, as well as 33 ready-to-use presentations. The book contains original material that has been class-tested by the author and numerous cases are examined in a biological and medical context. Readers will also benefit from the inclusion of: A thorough introduction to biological evolution, including the emergence of life, classifications and some known theories and molecular mechanisms A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields An examination of information and entropy, including sequence logos and explanations related to their meaning An exploration of the current state of bioinformatics, including what is known and what issues are usually avoided in the field A chapter on philosophical transactions that allows the reader a broader view of the prediction process Native computer implementations in the context of the field of Bioinformatics Extensive worked examples with detailed case studies that point out the meaning of different results Perfect for professionals and researchers in biology, medicine, engineering, and information technology, as well as upper level undergraduate students in these fields, Algorithms in Bioinformatics: Theory and Implementation will also earn a place in the libraries of software engineers who wish to understand how to implement bioinformatic algorithms in their products.
Introduction To Bioinformatics
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Author : Stephen A. Krawetz
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-01-31
Introduction To Bioinformatics written by Stephen A. Krawetz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-31 with Computers categories.
CD-ROM contains: chapter illustrations -- full and trial versions of programs.