Computational Exome And Genome Analysis

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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.

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

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 Immunology

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Author : Shyamasree Ghosh
language : en
Publisher: CRC Press
Release Date : 2020-01-31

Computational Immunology written by Shyamasree Ghosh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Medical categories.

Computational Immunology: Applications focuses on different mathematical models, statistical tools, techniques, and computational modelling that helps in understanding complex phenomena of the immune system and its biological functions. The book also focuses on the latest developments in computational biology in designing of drugs, targets, biomarkers for early detection and prognosis of a disease. It highlights the applications of computational methods in deciphering the complex processes of the immune system and its role in health and disease. This book discusses the most essential topics, including Next generation sequencing (NGS) and computational immunology Computational modelling and biology of diseases Drug designing Computation and identification of biomarkers Application in organ transplantation Application in disease detection and therapy Computational methods and applications in understanding of the invertebrate immune system S Ghosh is MSc, PhD, PGDHE, PGDBI, is PhD from IICB, CSIR, Kolkata, awarded the prestigious National Scholarship from the Government of India. She has worked and published extensively in glycobiology, sialic acids, immunology, stem cells and nanotechnology. She has authored several publications that include books and encyclopedia chapters in reputed journals and books.

Analyzing High Dimensional Gene Expression And Dna Methylation Data With R

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Author : Hongmei Zhang
language : en
Publisher: CRC Press
Release Date : 2020-05-14

Analyzing High Dimensional Gene Expression And Dna Methylation Data With R written by Hongmei Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-14 with Computers categories.

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline" of analytical methods with concrete examples starting from raw gene expression and DNA methylation data at the genome scale. Methods on quality control, data pre-processing, data mining, and further assessments are presented in the book, and R programs based on simulated data and real data are included. Codes with example data are all reproducible. Features: • Provides a sequence of analytical tools for genome-scale gene expression data and DNA methylation data, starting from quality control and pre-processing of raw genome-scale data. • Organized by a parallel presentation with explanation on statistical methods and corresponding R packages/functions in quality control, pre-processing, and data analyses (e.g., clustering and networks). • Includes source codes with simulated and real data to reproduce the results. Readers are expected to gain the ability to independently analyze genome-scaled expression and methylation data and detect potential biomarkers. This book is ideal for students majoring in statistics, biostatistics, and bioinformatics and researchers with an interest in high dimensional genetic and epigenetic studies.

Computational Biology And Bioinformatics

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Author : Ka-Chun Wong
language : en
Publisher: CRC Press
Release Date : 2016-04-27

Computational Biology And Bioinformatics written by Ka-Chun Wong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-27 with Science categories.

The advances in biotechnology such as the next generation sequencing technologies are occurring at breathtaking speed. Advances and breakthroughs give competitive advantages to those who are prepared. However, the driving force behind the positive competition is not only limited to the technological advancement, but also to the companion data analy

Biological Sequence Analysis

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Author : Richard Durbin
language : en
Publisher: Cambridge University Press
Release Date : 1998-04-23

Biological Sequence Analysis written by Richard Durbin 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 1998-04-23 with Medical categories.

Presents up-to-date computer methods for analysing DNA, RNA and protein sequences.

Stochastic Modelling For Systems Biology Third Edition

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Author : Darren J. Wilkinson
language : en
Publisher: CRC Press
Release Date : 2018-12-07

Stochastic Modelling For Systems Biology Third Edition written by Darren J. Wilkinson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Mathematics categories.

Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.

Encyclopedia Of Bioinformatics And Computational Biology

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Author :
language : en
Publisher: Elsevier
Release Date : 2018-08-21

Encyclopedia Of Bioinformatics And Computational Biology written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-21 with Medical categories.

Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

Medical And Health Genomics

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Author : Dhavendra Kumar
language : en
Publisher: Academic Press
Release Date : 2016-06-04

Medical And Health Genomics written by Dhavendra Kumar and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-04 with Science categories.

Medical and Health Genomics provides concise and evidence-based technical and practical information on the applied and translational aspects of genome sciences and the technologies related to non-clinical medicine and public health. Coverage is based on evolving paradigms of genomic medicine—in particular, the relation to public and population health genomics now being rapidly incorporated in health management and administration, with further implications for clinical population and disease management. - Provides extensive coverage of the emergent field of health genomics and its huge relevance to healthcare management - Presents user-friendly language accompanied by explanatory diagrams, figures, and many references for further study - Covers the applied, but non-clinical, sciences across disease discovery, genetic analysis, genetic screening, and prevention and management - Details the impact of clinical genomics across a diverse array of public and community health issues, and within a variety of global healthcare systems