Mathematics of Bioinformatics

Mathematics of Bioinformatics PDF Author: Matthew He
Publisher: John Wiley & Sons
ISBN: 1118099524
Category : Computers
Languages : en
Pages : 231

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Book Description
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.

Mathematics of Bioinformatics

Mathematics of Bioinformatics PDF Author: Matthew He
Publisher: John Wiley & Sons
ISBN: 1118099524
Category : Computers
Languages : en
Pages : 231

Get Book Here

Book Description
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.

Introduction to Mathematical Methods in Bioinformatics

Introduction to Mathematical Methods in Bioinformatics PDF Author: Alexander Isaev
Publisher: Springer Science & Business Media
ISBN: 9783540219736
Category : Science
Languages : en
Pages : 316

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Book Description
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.

Theory and Mathematical Methods in Bioinformatics

Theory and Mathematical Methods in Bioinformatics PDF Author: Shiyi Shen
Publisher: Springer Science & Business Media
ISBN: 3540748911
Category : Science
Languages : en
Pages : 450

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Book Description
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.

Pattern Discovery in Bioinformatics

Pattern Discovery in Bioinformatics PDF Author: Laxmi Parida
Publisher: CRC Press
ISBN: 1420010735
Category : Computers
Languages : en
Pages : 512

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Book Description
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

Statistical Methods in Bioinformatics PDF Author: Warren J. Ewens
Publisher: Springer Science & Business Media
ISBN: 0387400826
Category : Science
Languages : en
Pages : 616

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Book Description
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)

Algebraic and Discrete Mathematical Methods for Modern Biology

Algebraic and Discrete Mathematical Methods for Modern Biology PDF Author: Raina Robeva
Publisher: Academic Press
ISBN: 0128012714
Category : Mathematics
Languages : en
Pages : 383

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Book Description
Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems. Each chapter begins with a question from modern biology, followed by the description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set. This book is appropriate for mathematics courses such as finite mathematics, discrete structures, linear algebra, abstract/modern algebra, graph theory, probability, bioinformatics, statistics, biostatistics, and modeling, as well as for biology courses such as genetics, cell and molecular biology, biochemistry, ecology, and evolution. - Examines significant questions in modern biology and their mathematical treatments - Presents important mathematical concepts and tools in the context of essential biology - Features material of interest to students in both mathematics and biology - Presents chapters in modular format so coverage need not follow the Table of Contents - Introduces projects appropriate for undergraduate research - Utilizes freely accessible software for visualization, simulation, and analysis in modern biology - Requires no calculus as a prerequisite - Provides a complete Solutions Manual - Features a companion website with supplementary resources

Sequence Comparison

Sequence Comparison PDF Author: Kun-Mao Chao
Publisher: Springer Science & Business Media
ISBN: 184800320X
Category : Computers
Languages : en
Pages : 218

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Book Description
Biomolecular sequence comparison is the origin of bioinformatics. This book gives a complete in-depth treatment of the study of sequence comparison. A comprehensive introduction is followed by a focus on alignment algorithms and techniques, proceeded by a discussion of the theory. The book examines alignment methods and techniques, features a new issue of sequence comparison - the spaced seed technique, addresses several new flexible strategies for coping with various scoring schemes, and covers the theory on the significance of high-scoring segment pairs between two unalignment sequences. Useful appendices on basic concepts in molecular biology, primer in statistics and software for sequence alignment are included in this reader-friendly text, as well as chapter-ending exercise and research questions A state-of-the-art study of sequence alignment and homology search, this is an ideal reference for advanced students studying bioinformatics and will appeal to biologists who wish to know how to use homology search tools.

Introduction to Bioinformatics

Introduction to Bioinformatics PDF Author: Anna Tramontano
Publisher: CRC Press
ISBN: 1420010883
Category : Science
Languages : en
Pages : 193

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Book Description
Guiding readers from the elucidation and analysis of a genomic sequence to the prediction of a protein structure and the identification of the molecular function, Introduction to Bioinformatics describes the rationale and limitations of the bioinformatics methods and tools that can help solve biological problems. Requiring only a limited mathematical and statistical background, the book shows how to efficiently apply these approaches to biological data and evaluate the resulting information. The author, an expert bioinformatics researcher, first addresses the ways of storing and retrieving the enormous amount of biological data produced every day and the methods of decrypting the information encoded by a genome. She then covers the tools that can detect and exploit the evolutionary and functional relationships among biological elements. Subsequent chapters illustrate how to predict the three-dimensional structure of a protein. The book concludes with a discussion of the future of bioinformatics. Even though the future will undoubtedly offer new tools for tackling problems, most of the fundamental aspects of bioinformatics will not change. This resource provides the essential information to understand bioinformatics methods, ultimately facilitating in the solution of biological problems.

Bioinformatics and the Cell

Bioinformatics and the Cell PDF Author: Xuhua Xia
Publisher: Springer Science & Business Media
ISBN:
Category : Science
Languages : en
Pages : 376

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Book Description
Biological and biomedical sciences are becoming more interdisciplinary, and scientists of the future need inte rdisciplinary training instead of the conventional disciplinary training. Just as Sean Eddy (2005) wiselypointed out that sending monolingual diplomats to the United Nations maynot enhance international collaborations, combining strictly disciplinary scientists trained in either mathematics, computational science or molecular biology will not create a productive inte rdisciplinary team ready to solve interdisciplinary problems. Molecular biology is an interdiscip linary science back in its heyday, and founders of molecular biology were ofte n interdisciplinary scientists. Indeed, Francis Crick considered himself as “a mixture of crystallographer, biophysicist, biochemist, and geneticist” (Crick, 1965). Because it was too cumbersome to explain to people that he was such a mixture, the term “molecular biologist” came handy. To get the crystallographer, biophysicist, biochemist, and geneticist within hi mself to collaborate with each other probably worked better than a team with a crystallographer, a biophysicist, a biochemist and a geneticist who maynot even be interested in each other’s problems.

Bayesian Methods in Structural Bioinformatics

Bayesian Methods in Structural Bioinformatics PDF Author: Thomas Hamelryck
Publisher: Springer
ISBN: 3642272258
Category : Medical
Languages : en
Pages : 399

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Book Description
This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.