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Modeling Evolution Using Probabilistic Methods
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Book Synopsis Probability Models for DNA Sequence Evolution by : Rick Durrett
Download or read book Probability Models for DNA Sequence Evolution written by Rick Durrett and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: "What underlying forces are responsible for the observed patterns of variability, given a collection of DNA sequences?" In approaching this question a number of probability models are introduced and anyalyzed.Throughout the book, the theory is developed in close connection with data from more than 60 experimental studies that illustrate the use of these results.
Book Synopsis Biological Sequence Analysis by : Richard Durbin
Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Book Synopsis A Biologist's Guide to Mathematical Modeling in Ecology and Evolution by : Sarah P. Otto
Download or read book A Biologist's Guide to Mathematical Modeling in Ecology and Evolution written by Sarah P. Otto and published by Princeton University Press. This book was released on 2011-09-19 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available
Book Synopsis The Probabilistic Method by : Noga Alon
Download or read book The Probabilistic Method written by Noga Alon and published by John Wiley & Sons. This book was released on 2015-11-02 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.
Book Synopsis Evolutionary Genomics by : Maria Anisimova
Download or read book Evolutionary Genomics written by Maria Anisimova and published by Humana Press. This book was released on 2012-03-08 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: Together with early theoretical work in population genetics, the debate on sources of genetic makeup initiated by proponents of the neutral theory made a solid contribution to the spectacular growth in statistical methodologies for molecular evolution. Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies. Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of articles encompassing theoretical works and hands-on tutorials, as well as many reviews with key biological insight. Volume 2 begins with phylogenomics and continues with in-depth coverage of natural selection, recombination, and genomic innovation. The remaining chapters treat topics of more recent interest, including population genomics, -omics studies, and computational issues related to the handling of large-scale genomic data. Written in the highly successful Methods in Molecular BiologyTM series format, this work provides the kind of advice on methodology and implementation that is crucial for getting ahead in genomic data analyses. Comprehensive and cutting-edge, Evolutionary Genomics: Statistical and Computational Methods is a treasure chest of state-of the-art methods to study genomic and omics data, certain to inspire both young and experienced readers to join the interdisciplinary field of evolutionary genomics.
Book Synopsis Probabilistic Modeling in Bioinformatics and Medical Informatics by : Dirk Husmeier
Download or read book Probabilistic Modeling in Bioinformatics and Medical Informatics written by Dirk Husmeier and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.
Book Synopsis Evolutionary Equations with Applications in Natural Sciences by : Jacek Banasiak
Download or read book Evolutionary Equations with Applications in Natural Sciences written by Jacek Banasiak and published by Springer. This book was released on 2014-11-07 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the unifying theme of abstract evolutionary equations, both linear and nonlinear, in a complex environment, the book presents a multidisciplinary blend of topics, spanning the fields of theoretical and applied functional analysis, partial differential equations, probability theory and numerical analysis applied to various models coming from theoretical physics, biology, engineering and complexity theory. Truly unique features of the book are: the first simultaneous presentation of two complementary approaches to fragmentation and coagulation problems, by weak compactness methods and by using semigroup techniques, comprehensive exposition of probabilistic methods of analysis of long term dynamics of dynamical systems, semigroup analysis of biological problems and cutting edge pattern formation theory. The book will appeal to postgraduate students and researchers specializing in applications of mathematics to problems arising in natural sciences and engineering.
Book Synopsis Statistical Methods in Molecular Evolution by : Rasmus Nielsen
Download or read book Statistical Methods in Molecular Evolution written by Rasmus Nielsen and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the field of molecular evolution, inferences about past evolutionary events are made using molecular data from currently living species. With the availability of genomic data from multiple related species, molecular evolution has become one of the most active and fastest growing fields of study in genomics and bioinformatics. Most studies in molecular evolution rely heavily on statistical procedures based on stochastic process modelling and advanced computational methods including high-dimensional numerical optimization and Markov Chain Monte Carlo. This book provides an overview of the statistical theory and methods used in studies of molecular evolution. It includes an introductory section suitable for readers that are new to the field, a section discussing practical methods for data analysis, and more specialized sections discussing specific models and addressing statistical issues relating to estimation and model choice. The chapters are written by the leaders of field and they will take the reader from basic introductory material to the state-of-the-art statistical methods. This book is suitable for statisticians seeking to learn more about applications in molecular evolution and molecular evolutionary biologists with an interest in learning more about the theory behind the statistical methods applied in the field. The chapters of the book assume no advanced mathematical skills beyond basic calculus, although familiarity with basic probability theory will help the reader. Most relevant statistical concepts are introduced in the book in the context of their application in molecular evolution, and the book should be accessible for most biology graduate students with an interest in quantitative methods and theory. Rasmus Nielsen received his Ph.D. form the University of California at Berkeley in 1998 and after a postdoc at Harvard University, he assumed a faculty position in Statistical Genomics at Cornell University. He is currently an Ole Rømer Fellow at the University of Copenhagen and holds a Sloan Research Fellowship. His is an associate editor of the Journal of Molecular Evolution and has published more than fifty original papers in peer-reviewed journals on the topic of this book. From the reviews: "...Overall this is a very useful book in an area of increasing importance." Journal of the Royal Statistical Society "I find Statistical Methods in Molecular Evolution very interesting and useful. It delves into problems that were considered very difficult just several years ago...the book is likely to stimulate the interest of statisticians that are unaware of this exciting field of applications. It is my hope that it will also help the 'wet lab' molecular evolutionist to better understand mathematical and statistical methods." Marek Kimmel for the Journal of the American Statistical Association, September 2006 "Who should read this book? We suggest that anyone who deals with molecular data (who does not?) and anyone who asks evolutionary questions (who should not?) ought to consult the relevant chapters in this book." Dan Graur and Dror Berel for Biometrics, September 2006 "Coalescence theory facilitates the merger of population genetics theory with phylogenetic approaches, but still, there are mostly two camps: phylogeneticists and population geneticists. Only a few people are moving freely between them. Rasmus Nielsen is certainly one of these researchers, and his work so far has merged many population genetic and phylogenetic aspects of biological research under the umbrella of molecular evolution. Although Nielsen did not contribute a chapter to his book, his work permeates all its chapters. This book gives an overview of his interests and current achievements in molecular evolution. In short, this book should be on your bookshelf." Peter Beerli for Evolution, 60(2), 2006
Book Synopsis Probabilistic Methods for Bioinformatics by : Richard E. Neapolitan
Download or read book Probabilistic Methods for Bioinformatics written by Richard E. Neapolitan and published by Morgan Kaufmann. This book was released on 2009-06-12 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis. - Unique coverage of probabilistic reasoning methods applied to bioinformatics data--those methods that are likely to become the standard analysis tools for bioinformatics. - Shares insights about when and why probabilistic methods can and cannot be used effectively; - Complete review of Bayesian networks and probabilistic methods with a practical approach.
Book Synopsis Models and Methods for Biological Evolution by : Gilles Didier
Download or read book Models and Methods for Biological Evolution written by Gilles Didier and published by John Wiley & Sons. This book was released on 2024-04-10 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological evolution is the phenomenon concerning how species are born, are transformed or disappear over time. Its study relies on sophisticated methods that involve both mathematical modeling of the biological processes at play and the design of efficient algorithms to fit these models to genetic and morphological data. Models and Methods for Biological Evolution outlines the main methods to study evolution and provides a broad overview illustrating the variety of formal approaches used, notably including combinatorial optimization, stochastic models and statistical inference techniques. Some of the most relevant applications of these methods are detailed, concerning, for example, the study of migratory events of ancient human populations or the progression of epidemics. This book should thus be of interest to applied mathematicians interested in central problems in biology, and to biologists eager to get a deeper understanding of widely used techniques of evolutionary data analysis.
Book Synopsis Atlas of Protein Sequence and Structure by :
Download or read book Atlas of Protein Sequence and Structure written by and published by . This book was released on 1973 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sequence — Evolution — Function by : Eugene V. Koonin
Download or read book Sequence — Evolution — Function written by Eugene V. Koonin and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.
Book Synopsis Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities by : Tadlaoui, Mouenis Anouar
Download or read book Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities written by Tadlaoui, Mouenis Anouar and published by IGI Global. This book was released on 2018-11-16 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Teachers use e-learning systems to develop course notes and web-based activities to communicate with learners on one side and monitor and classify their progress on the other. Learners use it for learning, communication, and collaboration. Adaptive e-learning systems often employ learner models, and the behavior of an adaptive system varies depending on the data from the learner model and the learner's profile. Without knowing anything about the learner who uses the system, a system would behave in exactly the same way for all learners. Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities is a collection of research on the use of Bayesian networks and methods as a probabilistic formalism for the management of the learner model in adaptive hypermedia. It specifically discusses comparative studies, transformation rules, and case diagrams that support all phases of the learner model and the use of Bayesian networks and multi-entity Bayesian networks to manage dynamic aspects of this model. While highlighting topics such as developing the learner model, learning management systems, and modeling techniques, this book is ideally designed for instructional designers, course administrators, educators, researchers, and professionals.
Download or read book Bioinformatics written by Ron D. Appel and published by World Scientific. This book was released on 2009 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological research and recent technological advances have resulted in an enormous increase in research data that require large storage capacities, powerful computing resources, and accurate data analysis algorithms. Bioinformatics is the field that provides these resources to life science researchers. The Swiss Institute of Bioinformatics (SIB), which has celebrated its 10th anniversary in 2008, is an institution of national importance, recognized worldwide for its state-of-the-art work. Organized as a federation of bioinformatics research groups from Swiss universities and research institutes, the SIB provides services to the life science community that are highly appreciated worldwide, and coordinates research and education in bioinformatics nationwide. The SIB plays a central role in life science research both in Switzerland and abroad by developing extensive and high-quality bioinformatics resources that are essential for all life scientists. Knowledge developed by SIB members in areas such as genomics, proteomics, and systems biology is directly transformed by academia and industry into innovative solutions to improve global health. Such an astounding concentration of talent in a given field is unusual and unique in Switzerland. This book provides an insight into some of the key areas of activity in bioinformatics in Switzerland. With contributions from SIB members, it covers both research work and major infrastructure efforts in genome and gene expression analysis, investigations on proteins and proteomes, evolutionary bioinformatics, and modeling of biological systems.
Book Synopsis Probability and Statistical Models with Applications by : CH. A. Charalambides
Download or read book Probability and Statistical Models with Applications written by CH. A. Charalambides and published by CRC Press. This book was released on 2000-09-21 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph of carefully collected articles reviews recent developments in theoretical and applied statistical science, highlights current noteworthy results and illustrates their applications; and points out possible new directions to pursue. With its enlightening account of statistical discoveries and its numerous figures and tables, Probabili
Book Synopsis Pattern Recognition in Computational Molecular Biology by : Mourad Elloumi
Download or read book Pattern Recognition in Computational Molecular Biology written by Mourad Elloumi and published by John Wiley & Sons. This book was released on 2015-12-24 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.
Book Synopsis Processes of Organic Evolution by : George Ledyard Stebbins
Download or read book Processes of Organic Evolution written by George Ledyard Stebbins and published by . This book was released on 1973 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt:
