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Computational Genome Analysis By Alignment


Computational Genome Analysis By Alignment
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Computational Genome Analysis


Computational Genome Analysis
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Author : Richard C. Deonier
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-27

Computational Genome Analysis written by Richard C. Deonier and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-27 with Science categories.


Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field. This book features: - Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variation - Presentation of fundamentals of probability, statistics, and algorithms - Implementation of computational methods with numerous examples based upon the R statistics package - Extensive descriptions and explanations to complement the analytical development - More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature - Exercises at the end of chapters From the reviews: "The book is useful for its breadth. An impressive variety of topics are surveyed...." Short Book Reviews of the ISI, June 2006 "It is a very good book indeed and I would strongly recommend it both to the student hoping to take this study further and to the general reader who wants to know what computational genome analysis is all about." Mark Bloom for the JRSS, Series A, Volume 169, p. 1006, October 2006 "Richard C. Deonier, Simon Tavare and Michael S. Waterman provide us wtih a 'roll up your sleeves and get dirty' (as the authors phrase it in their preface) introduction to the field of computational genome analysis...The book is carefully written and carefully edited..." Ralf Schmid for Genetic Research, Volume 87, p. 218, 2006



Computational Genome Analysis By Alignment


Computational Genome Analysis By Alignment
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Author : Yi Yang
language : en
Publisher:
Release Date : 2005

Computational Genome Analysis By Alignment written by Yi Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.




Computational Analysis Of Genome Evolution


Computational Analysis Of Genome Evolution
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Author : Aaron E. Darling
language : en
Publisher:
Release Date : 2006

Computational Analysis Of Genome Evolution written by Aaron E. Darling and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.




Computational Genomics With R


Computational Genomics With R
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Author : Altuna Akalin
language : en
Publisher: CRC Press
Release Date : 2020-12-16

Computational Genomics With R written by Altuna Akalin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-16 with Mathematics categories.


Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.



Computational Exome And Genome Analysis


Computational Exome And Genome Analysis
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Author : Peter Nicholas Robinson
language : en
Publisher: Chapman & Hall/CRC Mathematical and Computational Biology
Release Date : 2017

Computational Exome And Genome Analysis written by Peter Nicholas Robinson and has been published by Chapman & Hall/CRC Mathematical and Computational Biology this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Computational biology categories.


Cover -- Half Title -- Series Editor -- Published Titles -- Title -- Copyright -- Dedication -- Contents -- Who is this book for? -- Preface -- Contributors -- Part I Introduction -- Chapter 1 Introduction: Whole Exome and Genome Sequencing -- Chapter 2 NGS Technology -- Chapter 3 Illumina Technology -- Chapter 4 Data -- Part II Raw Data Processing -- Chapter 5 FASTQ Format -- Chapter 6 Raw Data: Quality Control -- Chapter 7 Trimming -- Part III Alignment -- Chapter 8 Alignment: Mapping Reads to the Reference Genome -- Chapter 9 SAM/BAM Format -- Chapter 10 Postprocessing the Alignment -- Chapter 11 Alignment Data: Quality Control -- Part IV Variant Calling -- Chapter 12 Variant Calling and Quality- Based Filtering -- Chapter 13 Variant Call Format (VCF) -- Chapter 14 Jannovar -- Chapter 15 Variant Annotation -- Chapter 16 Variant Calling: Quality Control -- Chapter 17 Integrative Genomics Viewer (IGV): Visualizing Alignments and Variants -- Chapter 18 De Novo Variants -- Chapter 19 Structural Variation -- Part V Variant Filtering -- Chapter 20 Pedigree and Linkage Analysis -- Chapter 21 Intersection Analysis and Rare Variant Association Studies -- Chapter 22 Variant Frequency Analysis -- Chapter 23 Variant Pathogenicity Prediction -- Part VI Prioritization -- Chapter 24 Variant Prioritization -- Chapter 25 Prioritization by Random Walk Analysis -- Chapter 26 Phenotype Analysis -- Chapter 27 Exomiser and Genomiser -- Chapter 28 Medical Interpretation -- Part VII Cancer -- Chapter 29 A (Very) Short Introduction to Cancer -- Chapter 30 Somatic Variants in Cancer -- Chapter 31 Tumor Evolution and Sample Purity -- Chapter 32 Driver Mutations and Mutational Signatures -- Appendix A Hints and Answers -- References -- Index



Statistical And Computational Challenges In Molecular Phylogenetics And Evolution


Statistical And Computational Challenges In Molecular Phylogenetics And Evolution
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Author : Royal Society (Great Britain). Discussion Meeting
language : en
Publisher:
Release Date : 2008

Statistical And Computational Challenges In Molecular Phylogenetics And Evolution written by Royal Society (Great Britain). Discussion Meeting and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Cognitive neuroscience categories.




Computational Gene Annotation And Protein Evolution Analysis


Computational Gene Annotation And Protein Evolution Analysis
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Author : Samir Pandurangi
language : en
Publisher:
Release Date : 2004

Computational Gene Annotation And Protein Evolution Analysis written by Samir Pandurangi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.




A Bioinformatics Discovery Oriented Computing Framework


A Bioinformatics Discovery Oriented Computing Framework
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Author : Jake Yue Chen
language : en
Publisher:
Release Date : 2001

A Bioinformatics Discovery Oriented Computing Framework written by Jake Yue Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.




Introduction To Computational Genomics


Introduction To Computational Genomics
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Author : Nello Cristianini
language : en
Publisher: Cambridge University Press
Release Date : 2006-12-14

Introduction To Computational Genomics written by Nello Cristianini and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-14 with Computers categories.


Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.



Computational Exome And Genome Analysis


Computational Exome And Genome Analysis
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Author : Peter N. Robinson
language : en
Publisher: CRC Press
Release Date : 2017-09-13

Computational Exome And Genome Analysis written by Peter N. Robinson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-13 with Computers categories.


Exome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinformatics. Computational Exome and Genome Analysis provides a practical introduction to all of the major areas in the field, enabling readers to develop a comprehensive understanding of the sequencing process and the entire computational analysis pipeline.