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Author: Mark Borodovsky
Publisher: Cambridge University Press
ISBN: 1139458124
Category : Science
Languages : en
Pages : 15
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Book Description
This book is the first of its kind to provide a large collection of bioinformatics problems with accompanying solutions. Notably, the problem set includes all of the problems offered in Biological Sequence Analysis, by Durbin et al. (Cambridge, 1998), widely adopted as a required text for bioinformatics courses at leading universities worldwide. Although many of the problems included in Biological Sequence Analysis as exercises for its readers have been repeatedly used for homework and tests, no detailed solutions for the problems were available. Bioinformatics instructors had therefore frequently expressed a need for fully worked solutions and a larger set of problems for use on courses. This book provides just that: following the same structure as Biological Sequence Analysis and significantly extending the set of workable problems, it will facilitate a better understanding of the contents of the chapters in BSA and will help its readers develop problem-solving skills that are vitally important for conducting successful research in the growing field of bioinformatics. All of the material has been class-tested by the authors at Georgia Tech, where the first ever MSc degree program in Bioinformatics was held.
Author: Mark Borodovsky
Publisher: Cambridge University Press
ISBN: 1139458124
Category : Science
Languages : en
Pages : 15
Get Book
Book Description
This book is the first of its kind to provide a large collection of bioinformatics problems with accompanying solutions. Notably, the problem set includes all of the problems offered in Biological Sequence Analysis, by Durbin et al. (Cambridge, 1998), widely adopted as a required text for bioinformatics courses at leading universities worldwide. Although many of the problems included in Biological Sequence Analysis as exercises for its readers have been repeatedly used for homework and tests, no detailed solutions for the problems were available. Bioinformatics instructors had therefore frequently expressed a need for fully worked solutions and a larger set of problems for use on courses. This book provides just that: following the same structure as Biological Sequence Analysis and significantly extending the set of workable problems, it will facilitate a better understanding of the contents of the chapters in BSA and will help its readers develop problem-solving skills that are vitally important for conducting successful research in the growing field of bioinformatics. All of the material has been class-tested by the authors at Georgia Tech, where the first ever MSc degree program in Bioinformatics was held.
Author: Richard Durbin
Publisher: Cambridge University Press
ISBN: 113945739X
Category : Science
Languages : en
Pages : 372
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Book Description
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.
Author: Richard Durbin
Publisher: Cambridge University Press
ISBN: 9780521629713
Category : Science
Languages : en
Pages : 372
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Book Description
Presents up-to-date computer methods for analysing DNA, RNA and protein sequences.
Author: Ken Nguyen
Publisher: John Wiley & Sons
ISBN: 1118229045
Category : Computers
Languages : en
Pages : 256
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Book Description
Covers the fundamentals and techniques of multiple biological sequence alignment and analysis, and shows readers how to choose the appropriate sequence analysis tools for their tasks This book describes the traditional and modern approaches in biological sequence alignment and homology search. This book contains 11 chapters, with Chapter 1 providing basic information on biological sequences. Next, Chapter 2 contains fundamentals in pair-wise sequence alignment, while Chapters 3 and 4 examine popular existing quantitative models and practical clustering techniques that have been used in multiple sequence alignment. Chapter 5 describes, characterizes and relates many multiple sequence alignment models. Chapter 6 describes how traditionally phylogenetic trees have been constructed, and available sequence knowledge bases can be used to improve the accuracy of reconstructing phylogeny trees. Chapter 7 covers the latest methods developed to improve the run-time efficiency of multiple sequence alignment. Next, Chapter 8 covers several popular existing multiple sequence alignment server and services, and Chapter 9 examines several multiple sequence alignment techniques that have been developed to handle short sequences (reads) produced by the Next Generation Sequencing technique (NSG). Chapter 10 describes a Bioinformatics application using multiple sequence alignment of short reads or whole genomes as input. Lastly, Chapter 11 provides a review of RNA and protein secondary structure prediction using the evolution information inferred from multiple sequence alignments. • Covers the full spectrum of the field, from alignment algorithms to scoring methods, practical techniques, and alignment tools and their evaluations • Describes theories and developments of scoring functions and scoring matrices •Examines phylogeny estimation and large-scale homology search Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Applications is a reference for researchers, engineers, graduate and post-graduate students in bioinformatics, and system biology and molecular biologists. Ken Nguyen, PhD, is an associate professor at Clayton State University, GA, USA. He received his PhD, MSc and BSc degrees in computer science all from Georgia State University. His research interests are in databases, parallel and distribute computing and bioinformatics. He was a Molecular Basis of Disease fellow at Georgia State and is the recipient of the highest graduate honor at Georgia State, the William M. Suttles Graduate Fellowship. Xuan Guo, PhD, is a postdoctoral associate at Oak Ridge National Lab, USA. He received his PhD degree in computer science from Georgia State University in 2015. His research interests are in bioinformatics, machine leaning, and cloud computing. He is an editorial assistant of International Journal of Bioinformatics Research and Applications. Yi Pan, PhD, is a Regents' Professor of Computer Science and an Interim Associate Dean and Chair of Biology at Georgia State University. He received his BE and ME in computer engineering from Tsinghua University in China and his PhD in computer science from the University of Pittsburgh. Dr. Pan's research interests include parallel and distributed computing, optical networks, wireless networks and bioinformatics. He has published more than 180 journal papers with about 60 papers published in various IEEE/ACM journals. He is co-editor along with Albert Y. Zomaya of the Wiley Series in Bioinformatics.
Author: Michael S. Waterman
Publisher: CRC Press
ISBN: 1351437089
Category : Mathematics
Languages : en
Pages : 248
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Book Description
Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.
Author: Andreas Gogol-Döring
Publisher: CRC Press
ISBN: 1420076248
Category : Computers
Languages : en
Pages : 330
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Book Description
An Easy-to-Use Research Tool for Algorithm Testing and DevelopmentBefore 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 conc
Author: David W. Mount
Publisher:
ISBN:
Category : Amino acid sequence
Languages : en
Pages : 584
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Book Description
The application of computational methods to DNA and protein science is an exciting development in biology. Bioinformatics: Sequence and Genome Analysis is a comprehensive introduction to this emerging field of study. The book has many valuable features. It is written for biologists who want to understand methods of sequence and structure analysis and how the necessary computer programs work. Sequence alignment, structure prediction, phylogenetic and gene prediction, database searching, and genome analysis are clearly explained and illustrated. Underlying algorithms and assumptions are also explained for the non-specialist, and examples are presented in simple numerical terms rather than complex formulas and notation. Theoretical underpinnings are linked to biological problems and their solutions, while extensive tables provide descriptions and Web sources for a broad range of publicly available software. Based on the author's experience as a molecular geneticist and bioinformaticist at the University of Arizona, this is an educational book, useful as a laboratory reference for investigators and also as a teaching reference for graduate and undergraduate students.
Author: Robert M. Miura
Publisher: American Mathematical Soc.
ISBN: 9780821897119
Category : Science
Languages : en
Pages : 142
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Book Description
Several data banks around the world are accumulating DNA sequences at a feverish rate, with tremendous potential for furthering our knowledge of how biological systems code and pass on information. The sophisticated mathematical analysis of that data is just beginning. The Eighteenth Annual Symposium on Some Mathematical Questions in Biology was held in conjunction with the Annual Meeting of the AAAS and brought together speakers knowledgeable in both biology and mathematics to discuss these developments and to emphasize the need for rigorous, efficient computational tools. These computational tools include biologically relevant definitions of sequence similarity and string matching algorithms. The solutions for some of these problems have great generality; the string matching methods first developed for biological sequences have now been applied to areas such as geology, linguistics, and speech recognition. There is a great potential here for creating of new mathematics to handle this growing data base, with new applications for many areas of mathematics, computer science, and statistics.
Author: Tieng K. Yap
Publisher: Springer Science & Business Media
ISBN: 1461313910
Category : Computers
Languages : en
Pages : 219
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Book Description
High Performance Computational Methods for Biological Sequence Analysis presents biological sequence analysis using an interdisciplinary approach that integrates biological, mathematical and computational concepts. These concepts are presented so that computer scientists and biomedical scientists can obtain the necessary background for developing better algorithms and applying parallel computational methods. This book will enable both groups to develop the depth of knowledge needed to work in this interdisciplinary field. This work focuses on high performance computational approaches that are used to perform computationally intensive biological sequence analysis tasks: pairwise sequence comparison, multiple sequence alignment, and sequence similarity searching in large databases. These computational methods are becoming increasingly important to the molecular biology community allowing researchers to explore the increasingly large amounts of sequence data generated by the Human Genome Project and other related biological projects. The approaches presented by the authors are state-of-the-art and show how to reduce analysis times significantly, sometimes from days to minutes. High Performance Computational Methods for Biological Sequence Analysis is tremendously important to biomedical science students and researchers who are interested in applying sequence analyses to their studies, and to computational science students and researchers who are interested in applying new computational approaches to biological sequence analyses.
Author: Veli Mäkinen
Publisher: Cambridge University Press
ISBN: 1009341219
Category : Computers
Languages : en
Pages : 470
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Book Description
Guided by standard bioscience workflows in high-throughput sequencing analysis, this book for graduate students, researchers, and professionals in bioinformatics and computer science offers a unified presentation of genome-scale algorithms. This new edition covers the use of minimizers and other advanced data structures in pangenomics approaches.
