Bioinformatics Sequence Alignment and Markov Models

Author: Kal Sharma
Publisher: McGraw Hill Professional
ISBN: 0071593071
Format: PDF, ePub, Mobi
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GET FULLY UP-TO-DATE ON BIOINFORMATICS-THE TECHNOLOGY OF THE 21ST CENTURY Bioinformatics showcases the latest developments in the field along with all the foundational information you'll need. It provides in-depth coverage of a wide range of autoimmune disorders and detailed analyses of suffix trees, plus late-breaking advances regarding biochips and genomes. Featuring helpful gene-finding algorithms, Bioinformatics offers key information on sequence alignment, HMMs, HMM applications, protein secondary structure, microarray techniques, and drug discovery and development. Helpful diagrams accompany mathematical equations throughout, and exercises appear at the end of each chapter to facilitate self-evaluation. This thorough, up-to-date resource features: Worked-out problems illustrating concepts and models End-of-chapter exercises for self-evaluation Material based on student feedback Illustrations that clarify difficult math problems A list of bioinformatics-related websites Bioinformatics covers: Sequence representation and alignment Hidden Markov models Applications of HMMs Gene finding Protein secondary structure prediction Microarray techniques Drug discovery and development Internet resources and public domain databases

Biological Sequence Analysis

Author: Richard Durbin
Publisher: Cambridge University Press
ISBN: 113945739X
Format: PDF, Docs
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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.

Problems and Solutions in Biological Sequence Analysis

Author: Mark Borodovsky
Publisher: Cambridge University Press
ISBN: 1139458124
Format: PDF, ePub
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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 (BSA), by Durbin et al., widely adopted as a required text for bioinformatics courses at leading universities worldwide. Although many of the problems included in BSA 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 BSA 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 M.Sc. degree program in Bioinformatics was held.

Bioinformatics

Author: Source Wikipedia
Publisher: University-Press.org
ISBN: 9781230629612
Format: PDF, ePub, Mobi
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 294. Chapters: Proteomics, Hidden Markov model, Biostatistics, Proteome, Sequence alignment, Full genome sequencing, Rose[email protected], Metagenomics, Mass-spectrometry software, DNA microarray, Protein structure prediction, Homology modeling, Synthetic biology, Metabolomics, DNA barcoding, Multiple sequence alignment, Haplogroup M, Systems biology, Protein-protein interaction prediction, Flux balance analysis, Models of DNA evolution, Macromolecular docking, CaBIG, Metabolic network modelling, Substitution model, ChIP-on-chip, DNA binding site, Morphometrics, Personal genomics, Computational Resource for Drug Discovery, Biochip, Complex system biology, DNA sequencing theory, Sequence motif, UniProt, Protein subcellular localization prediction, Ionomics, Biopunk, 1000 Genomes Project, Statistical potential, Sequence assembly, Gene Ontology, List of biological databases, Demographic and Health Surveys, Gene prediction, Modelling biological systems, Shamkant Navathe, UCSC Genome Browser, Bioconductor, Precision and recall, Molecular modelling, Sequence profiling tool, FASTA format, Threading, Biclustering, John Quackenbush, Biomedical text mining, FASTQ format, Substitution matrix, Stockholm format, Interactome, CASP, Sensitivity and specificity, High-throughput screening, MicroRNA and microRNA target database, Scoring functions for docking, Minimum Information Standards, Genenetwork, Stochastic context-free grammar, Multiple displacement amplification, Virtual screening, List of phylogenetics software, Protein fragment library, World Health Imaging, Telemedicine, and Informatics Alliance, List of MeSH codes, Automated species identification, Ontology engineering, Gene nomenclature, Statistical coupling analysis, Suspension array technology, Sulston score, NeuroLex, Society for Mathematical Biology, Bayesian inference in phylogeny, ..

Sequence Alignment

Author: Michael S. Rosenberg
Publisher: Univ of California Press
ISBN: 9780520256972
Format: PDF, Docs
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The sequencing of the human genome involved thousands of scientists but used relatively few tools. Obtaining sequences is simpler, but aligning the sequences remains a complicated but underappreciated aspect of comparative molecular biology. This book discusses the practice of alignment, and the procedures by which alignments are established.

Understanding Bioinformatics

Author: Marketa J. Zvelebil
Publisher: Garland Science
ISBN: 9780815340249
Format: PDF, Mobi
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Suitable for advanced undergraduates & postgraduates, this book provides a definitive guide to bioinformatics. It takes a conceptual approach & guides the reader from first principles through to an understanding of the computational techniques & the key algorithms.

Introduction to Mathematical Methods in Bioinformatics

Author: Alexander Isaev
Publisher: Springer Science & Business Media
ISBN: 9783540219736
Format: PDF, ePub
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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.

Protein Homology Detection Through Alignment of Markov Random Fields

Author: Jinbo Xu
Publisher: Springer
ISBN: 3319149148
Format: PDF, Kindle
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This work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications. The text first surveys a few popular homology detection methods, such as Position-Specific Scoring Matrix (PSSM) and Hidden Markov Model (HMM) based methods, and then describes a novel Markov Random Fields (MRF) based method developed by the authors. MRF-based methods are much more sensitive than HMM- and PSSM-based methods for remote homolog detection and fold recognition, as MRFs can model long-range residue-residue interaction. The text also describes the installation, usage and result interpretation of programs implementing the MRF-based method.

Analysis of Phylogenetics and Evolution with R

Author: Emmanuel Paradis
Publisher: Springer Science & Business Media
ISBN: 1461417430
Format: PDF, ePub, Mobi
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The increasing availability of molecular and genetic databases coupled with the growing power of computers gives biologists opportunities to address new issues, such as the patterns of molecular evolution, and re-assess old ones, such as the role of adaptation in species diversification. In the second edition, the book continues to integrate a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists' data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments. The second edition is completed updated, covering the full gamut of R packages for this area that have been introduced to the market since its previous publication five years ago. There is also a new chapter on the simulation of evolutionary data. Graduate students and researchers in evolutionary biology can use this book as a reference for data analyses, whereas researchers in bioinformatics interested in evolutionary analyses will learn how to implement these methods in R. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered: manipulation of phylogenetic data, phylogeny estimation, tree drawing, phylogenetic comparative methods, and estimation of ancestral characters. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.