Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Handbook Of Hidden Markov Models In Bioinformatics
Download Handbook Of Hidden Markov Models In Bioinformatics full books in PDF, epub, and Kindle. Read online Handbook Of Hidden Markov Models In Bioinformatics ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Handbook of Hidden Markov Models in Bioinformatics by : Martin Gollery
Download or read book Handbook of Hidden Markov Models in Bioinformatics written by Martin Gollery and published by CRC Press. This book was released on 2008-06-12 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demonstrating that many useful resources, such as databases, can benefit most bioinformatics projects, the Handbook of Hidden Markov Models in Bioinformatics focuses on how to choose and use various methods and programs available for hidden Markov models (HMMs). The book begins with discussions on key HMM and related profile methods, including the HMMER package, the sequence analysis method (SAM), and the PSI-BLAST algorithm. It then provides detailed information about various types of publicly available HMM databases, such as Pfam, PANTHER, COG, and metaSHARK. After outlining ways to develop and use an automated bioinformatics workflow, the author describes how to make custom HMM databases using HMMER, SAM, and PSI-BLAST. He also helps you select the right program to speed up searches. The final chapter explores several applications of HMM methods, including predictions of subcellular localization, posttranslational modification, and binding site. By learning how to effectively use the databases and methods presented in this handbook, you will be able to efficiently identify features of biological interest in your data.
Book Synopsis Hidden Markov Models for Bioinformatics by : T. Koski
Download or read book Hidden Markov Models for Bioinformatics written by T. Koski and published by . This book was released on 2011-05-13 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Hidden Markov Models by : David R. Westhead
Download or read book Hidden Markov Models written by David R. Westhead and published by Humana Press. This book was released on 2018-07-12 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology. Hidden Markov Models: Methods and Protocols guides readers through chapters on biological systems; ranging from single biomolecule, cellular level, and to organism level and the use of HMMs in unravelling the complex mechanisms that govern these complex systems. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Hidden Markov Models: Methods and Protocols aims to demonstrate the impact of HMM in biology and inspire new research.
Book Synopsis Hidden Markov Models for Bioinformatics by : T. Koski
Download or read book Hidden Markov Models for Bioinformatics written by T. Koski and published by Springer. This book was released on 2001-12-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Algorithms in Bioinformatics by : Wing-Kin Sung
Download or read book Algorithms in Bioinformatics written by Wing-Kin Sung and published by CRC Press. This book was released on 2009-11-24 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions Developed from the author's own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the bi
Book Synopsis Handbook of Research on Systems Biology Applications in Medicine by : Daskalaki, Andriani
Download or read book Handbook of Research on Systems Biology Applications in Medicine written by Daskalaki, Andriani and published by IGI Global. This book was released on 2008-11-30 with total page 982 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book highlights the use of systems approaches including genomic, cellular, proteomic, metabolomic, bioinformatics, molecular, and biochemical, to address fundamental questions in complex diseases like cancer diabetes but also in ageing"--Provided by publisher.
Book Synopsis The Phylogenetic Handbook by : Marco Salemi
Download or read book The Phylogenetic Handbook written by Marco Salemi and published by Cambridge University Press. This book was released on 2009-03-26 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: A broad, hands on guide with detailed explanations of current methodology, relevant exercises and popular software tools.
Book Synopsis Mixture and Hidden Markov Models with R by : Ingmar Visser
Download or read book Mixture and Hidden Markov Models with R written by Ingmar Visser and published by Springer Nature. This book was released on 2022-06-28 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses mixture and hidden Markov models for modeling behavioral data. Mixture and hidden Markov models are statistical models which are useful when an observed system occupies a number of distinct “regimes” or unobserved (hidden) states. These models are widely used in a variety of fields, including artificial intelligence, biology, finance, and psychology. Hidden Markov models can be viewed as an extension of mixture models, to model transitions between states over time. Covering both mixture and hidden Markov models in a single book allows main concepts and issues to be introduced in the relatively simpler context of mixture models. After a thorough treatment of the theory and practice of mixture modeling, the conceptual leap towards hidden Markov models is relatively straightforward. This book provides many practical examples illustrating the wide variety of uses of the models. These examples are drawn from our own work in psychology, as well as other areas such as financial time series and climate data. Most examples illustrate the use of the authors’ depmixS4 package, which provides a flexible framework to construct and estimate mixture and hidden Markov models. All examples are fully reproducible and the accompanying hmmR package provides all the datasets used, as well as additional functionality. This book is suitable for advanced students and researchers with an applied background.
Book Synopsis Compact Handbook of Computational Biology by : A.K. Konopka
Download or read book Compact Handbook of Computational Biology written by A.K. Konopka and published by CRC Press. This book was released on 2004-08-30 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The assimilation of computational methods into the life sciences has played an important role in advancing biological research. From sequencing genomes to discovering motifs in large collections of functionally equivalent sequences of nucleic acids and proteins, the value of powerful computational tools has become abundantly clear. The Compact Hand
Book Synopsis Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R by : Gabriel Valiente
Download or read book Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R written by Gabriel Valiente and published by CRC Press. This book was released on 2009-04-08 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis of genomic, transcriptomic, proteomic, metabolomic, and interactomic data. It implements the algorithms in Perl and R, two widely used scripting languages in computational biology. The book provides a well-rounded explanation of traditional issues as well as an up-to-date account of more recent developments, such as graph similarity and search. It is organized around the specific algorithmic problems that arise when dealing with structures that are commonly found in computational biology, including biological sequences, trees, and graphs. For each of these structures, the author makes a clear distinction between problems that arise in the analysis of one structure and in the comparative analysis of two or more structures. He also presents phylogenetic trees and networks as examples of trees and graphs in computational biology. This book supplies a comprehensive view of the whole field of combinatorial pattern matching from a computational biology perspective. Along with thorough discussions of each biological problem, it includes detailed algorithmic solutions in pseudo-code, full Perl and R implementation, and pointers to other software, such as those on CPAN and CRAN.
Book Synopsis Game-Theoretical Models in Biology by : Mark Broom
Download or read book Game-Theoretical Models in Biology written by Mark Broom and published by CRC Press. This book was released on 2013-03-27 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the major topics of evolutionary game theory, Game-Theoretical Models in Biology presents both abstract and practical mathematical models of real biological situations. It discusses the static aspects of game theory in a mathematically rigorous way that is appealing to mathematicians. In addition, the authors explore many applications of game theory to biology, making the text useful to biologists as well. The book describes a wide range of topics in evolutionary games, including matrix games, replicator dynamics, the hawk-dove game, and the prisoner’s dilemma. It covers the evolutionarily stable strategy, a key concept in biological games, and offers in-depth details of the mathematical models. Most chapters illustrate how to use MATLAB® to solve various games. Important biological phenomena, such as the sex ratio of so many species being close to a half, the evolution of cooperative behavior, and the existence of adornments (for example, the peacock’s tail), have been explained using ideas underpinned by game theoretical modeling. Suitable for readers studying and working at the interface of mathematics and the life sciences, this book shows how evolutionary game theory is used in the modeling of these diverse biological phenomena.
Book Synopsis Handbook of Computational Molecular Biology by : Srinivas Aluru
Download or read book Handbook of Computational Molecular Biology written by Srinivas Aluru and published by CRC Press. This book was released on 2005-12-21 with total page 1108 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis G Protein-Coupled Receptors - Modeling and Simulation by : Marta Filizola
Download or read book G Protein-Coupled Receptors - Modeling and Simulation written by Marta Filizola and published by Springer Science & Business Media. This book was released on 2013-10-25 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: G protein-coupled receptors (GPCRs) are heptahelical transmembrane receptors that convert extra-cellular stimuli into intra-cellular signaling, and ultimately into biological responses. Since GPCRs are natural targets for approximately 40% of all modern medicines, it is not surprising that they have been the subject of intense research. Notwithstanding the amount of data generated over the years, discovering ligands of these receptors with optimal therapeutic properties is not straightforward and has certainly been hampered for years by the lack of high-resolution structural information about these receptors. Luckily, there has been a steady increase of high-resolution crystal structures of these receptors since 2007, and this information, integrated with dynamic inferences from computational and experimental methods, holds great potential for the discovery of new, improved drugs. This book, which provides, for the first time, state-of-the-art views on modeling and simulation of GPCRs, is divided into 4 parts. In the first part, the impact of currently available GPCR crystal structures on structural modeling is discussed extensively as are critical insights from simulations in the second part of the book. The third part reports recent progress in rational ligand discovery and mathematical modeling, whereas the fourth part provides an overview of bioinformatics tools and resources that are available for GPCRs.
Book Synopsis Statistical Modeling and Machine Learning for Molecular Biology by : Alan Moses
Download or read book Statistical Modeling and Machine Learning for Molecular Biology written by Alan Moses and published by CRC Press. This book was released on 2017-01-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Assumes no background in statistics or computers • Covers most major types of molecular biological data • Covers the statistical and machine learning concepts of most practical utility (P-values, clustering, regression, regularization and classification) • Intended for graduate students beginning careers in molecular biology, systems biology, bioengineering and genetics
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 Clustering in Bioinformatics and Drug Discovery by : John David MacCuish
Download or read book Clustering in Bioinformatics and Drug Discovery written by John David MacCuish and published by CRC Press. This book was released on 2010-11-15 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a DVD of color figures, Clustering in Bioinformatics and Drug Discovery provides an expert guide on extracting the most pertinent information from pharmaceutical and biomedical data. It offers a concise overview of common and recent clustering methods used in bioinformatics and drug discovery.Setting the stage for subsequent material, the firs
Book Synopsis Handbook of Mixture Analysis by : Sylvia Fruhwirth-Schnatter
Download or read book Handbook of Mixture Analysis written by Sylvia Fruhwirth-Schnatter and published by CRC Press. This book was released on 2019-01-04 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.
