Related books on 'sequence-analysis'Return to life science book list
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by: Jonathan Pevsner
publisher: Wiley-Blackwell, published: 2009-05-04
sales rank: 148977
The bestselling introduction to bioinformatics and functional genomics—now in an updated edition
Widely received in its previous edition, Bioinformatics and Functional Genomics offers the most broad-based introduction to this explosive new discipline. Now in a thoroughly updated and expanded Second Edition, it continues to be the go-to source for students and professionals involved in biomedical research.
This edition provides up-to-the-minute coverage of the fields of bioinformatics and genomics. Features new to this edition include:
The book is complemented by lavish illustrations and more than 500 figures and tables—fifty of which are entirely new to this edition. Each chapter includes a Problem Set, Pitfalls, Boxes explaining key techniques and mathematics/statistics principles, Summary, Recommended Reading, and a list of freely available software. Readers may visit a related Web page for supplemental information at www.wiley.com/go/pevsnerbioinformatics.
Bioinformatics and Functional Genomics, Second Edition serves as an excellent single-source textbook for advanced undergraduate and beginning graduate-level courses in the biological sciences and computer sciences. It is also an indispensable resource for biologists in a broad variety of disciplines who use the tools of bioinformatics and genomics to study particular research problems; bioinformaticists and computer scientists who develop computer algorithms and databases; and medical researchers and clinicians who want to understand the genomic basis of viral, bacterial, parasitic, or other diseases.
Praise for the first edition:
"...ideal both for biologists who want to master the application of bioinformatics to real-world problems and for computer scientists who need to understand the biological questions that motivate algorithms." Quarterly Review of Biology
"… an excellent textbook for graduate students and upper level undergraduate students." Annals of Biomedical Engineering
"…highly recommended for academic and medical libraries, and for researchers as an introduction and reference…" E-Streams
Biological Sequence Analysis Using the SeqAn C++ Library (Chapman & Hall/CRC Mathematical & Computational Biology)
by: Andreas Gogol-Döring
publisher: CRC Press, published: 2009-11-11
sales rank: 2837629
An Easy-to-Use Research Tool for Algorithm Testing and Development
Before the SeqAn project, there was clearly a lack of available implementations in sequence analysis, even for standard tasks. Implementations of needed algorithmic components were either unavailable or hard to access in third-party monolithic software products. Addressing these concerns, the developers of SeqAn created a comprehensive, easy-to-use, open source C++ library of efficient algorithms and data structures for the analysis of biological sequences. Written by the founders of this project, Biological Sequence Analysis Using the SeqAn C++ Library covers the SeqAn library, its documentation, and the supporting infrastructure.
The first part of the book describes the general library design. It introduces biological sequence analysis problems, discusses the benefit of using software libraries, summarizes the design principles and goals of SeqAn, details the main programming techniques used in SeqAn, and demonstrates the application of these techniques in various examples. Focusing on the components provided by SeqAn, the second part explores basic functionality, sequence data structures, alignments, pattern and motif searching, string indices, and graphs. The last part illustrates applications of SeqAn to genome alignment, consensus sequence in assembly projects, suffix array construction, and more.
This handy book describes a user-friendly library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn enables not only the implementation of new algorithms, but also the sound analysis and comparison of existing algorithms.
Visit SeqAn for more information.
by: Asuman G. Aksoy
publisher: Springer, published: 2009-12-17
sales rank: 709904
Today, nearly every undergraduate mathematics program requires at least one semester of real analysis. Often, students consider this course to be the most challenging or even intimidating of all their mathematics major requirements. The primary goal of A Problem Book in Real Analysis is to alleviate those concerns by systematically solving the problems related to the core concepts of most analysis courses. In doing so, the authors hope that learning analysis becomes less taxing and more satisfying.
The wide variety of exercises presented in this book range from the computational to the more conceptual and varies in difficulty. They cover the following subjects: set theory; real numbers; sequences; limits of the functions; continuity; differentiability; integration; series; metric spaces; sequences; and series of functions and fundamentals of topology. Furthermore, the authors define the concepts and cite the theorems used at the beginning of each chapter. A Problem Book in Real Analysis is not simply a collection of problems; it intends to stimulate its readers to independent thought in discovering analysis.
Prerequisites for accessing this book are a robust understanding of calculus and linear algebra.
Average Case Analysis of Algorithms on Sequences (Wiley Series in Discrete Mathematics and Optimization)
by: Wojciech Szpankowski
publisher: Wiley-Interscience, published: 2001-04-16
sales rank: 2274198
A timely book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume.
* Tools are illustrated through problems on words with applications to molecular biology, data compression, security, and pattern matching.
* Includes chapters on algorithms and data structures on words, probabilistic and analytical models, inclusion-exclusion principles, first and second moment methods, subadditive ergodic theorem and large deviations, elements of information theory, generating functions, complex asymptotic methods, Mellin transform and its applications, and analytic poissonization and depoissonization.
* Written by an established researcher with a strong international reputation in the field.
by: Ingvar Eidhammer
publisher: Wiley, published: 2004-02-13
sales rank: 2041186
Genomics and bioinformatics play an increasingly important and transformative role in medicine, society and agriculture. The mapping of the human genome has revealed 35,000 or so genes which might code for more than one protein, resulting in 100,000 proteins for the humans alone. Since proteins are attractive targets for developing drugs, efforts are now underway to map sequences and assign functions to many novel proteins. This book takes the novel approach to cover both the sequence and structure analysis of proteins in one volume and from an algorithmic perspective.
Key features of the book include:
Visit this website for exercises with solutions, computer programs, errata and additional material:
by: Matthew B. Miles
publisher: SAGE Publications, Inc, published: 2013-04-18
sales rank: 19045
The Third Edition of Miles & Huberman's classic research methods text is updated and streamlined by Johnny Saldaña, author of The Coding Manual for Qualitative Researchers. Several of the data display strategies from previous editions are now presented in re-envisioned and reorganized formats to enhance reader accessibility and comprehension. The Third Edition’s presentation of the fundamentals of research design and data management is followed by five distinct methods of analysis: exploring, describing, ordering, explaining, and predicting. Miles and Huberman's original research studies are profiled and accompanied with new examples from Saldaña's recent qualitative work. The book's most celebrated chapter, "Drawing and Verifying Conclusions," is retained and revised, and the chapter on report writing has been greatly expanded, and is now called “Writing About Qualitative Research.” Comprehensive and authoritative, Qualitative Data Analysis has been elegantly revised for a new generation of qualitative researchers.
by: Peter Duren
publisher: American Mathematical Society, published: 2012-06-06
sales rank: 654561
This book gives a rigorous treatment of selected topics in classical analysis, with many applications and examples. The exposition is at the undergraduate level, building on basic principles of advanced calculus without appeal to more sophisticated techniques of complex analysis and Lebesgue integration. Among the topics covered are Fourier series and integrals, approximation theory, Stirling's formula, the gamma function, Bernoulli numbers and polynomials, the Riemann zeta function, Tauberian theorems, elliptic integrals, ramifications of the Cantor set, and a theoretical discussion of differential equations including power series solutions at regular singular points, Bessel functions, hypergeometric functions, and Sturm comparison theory. Preliminary chapters offer rapid reviews of basic principles and further background material such as infinite products and commonly applied inequalities. This book is designed for individual study but can also serve as a text for second-semester courses in advanced calculus. Each chapter concludes with an abundance of exercises. Historical notes discuss the evolution of mathematical ideas and their relevance to physical applications. Special features are capsule scientific biographies of the major players and a gallery of portraits. Although this book is designed for undergraduate students, others may find it an accessible source of information on classical topics that underlie modern developments in pure and applied mathematics.
by: Stephen Winters-Hilt
publisher: Lulu.com, published: 2011-05-02
sales rank: 3435560
This is intended to be a simple and accessible book on machine learning methods and their application in computational genomics and nanopore transduction detection. This book has arisen from eight years of teaching one-semester courses on various machine-learning, cheminformatics, and bioinformatics topics. The book begins with a description of ad hoc signal acquisition methods and how to orient on signal processing problems with the standard tools from information theory and signal analysis. A general stochastic sequential analysis (SSA) signal processing architecture is then described that implements Hidden Markov Model (HMM) methods. Methods are then shown for classification and clustering using generalized Support Vector Machines, for use with the SSA Protocol, or independent of that approach. Optimization metaheuristics are used for tuning over algorithmic parameters throughout. Hardware implementations and short code examples of the various methods are also described.
by: Kevin P. Murphy
publisher: The MIT Press, published: 2012-08-24
sales rank: 16372
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
by: John McCleary
publisher: Cambridge University Press, published: 2000-11-27
sales rank: 1003500
Spectral sequences are among the most elegant and powerful methods of computation in mathematics. This book describes some of the most important examples of spectral sequences and some of their most spectacular applications. The first part treats the algebraic foundations for this sort of homological algebra, starting from informal calculations. The heart of the text is an exposition of the classical examples from homotopy theory, with chapters on the Leray-Serre spectral sequence, the Eilenberg-Moore spectral sequence, the Adams spectral sequence, and, in this new edition, the Bockstein spectral sequence. The last part of the book treats applications throughout mathematics, including the theory of knots and links, algebraic geometry, differential geometry and algebra. This is an excellent reference for students and researchers in geometry, topology, and algebra.