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Computational Genome Analysis


Computational Genome Analysis
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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 Computers categories.


This book 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 features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.



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 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.



Introduction To Computational Metagenomics


Introduction To Computational Metagenomics
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Author : Zhong Wang
language : en
Publisher: World Scientific
Release Date : 2022-04-11

Introduction To Computational Metagenomics written by Zhong Wang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-11 with Science categories.


Breakthroughs in high-throughput genome sequencing and high-performance computing technologies have empowered scientists to decode many genomes including our own. Now they have a bigger ambition: to fully understand the vast diversity of microbial communities within us and around us, and to exploit their potential for the improvement of our health and environment. In this new field called metagenomics, microbial genomes are sequenced directly from the habitats without lab cultivation. Computational metagenomics, however, faces both a data challenge that deals with tens of tera-bases of sequences and an algorithmic one that deals with the complexity of thousands of species and their interactions.This interdisciplinary book is essential reading for those who are interested in beginning their own journey in computational metagenomics. It is a prism to look through various intricate computational metagenomics problems and unravel their three distinctive aspects: metagenomics, data engineering, and algorithms. Graduate students and advanced undergraduates from genomics science or computer science fields will find that the concepts explained in this book can serve as stepping stones for more advanced topics, while metagenomics practitioners and researchers from similar disciplines may use it to broaden their knowledge or identify new research targets.



Applied Computational Genomics


Applied Computational Genomics
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Author : Yin Yao Shugart
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-30

Applied Computational Genomics written by Yin Yao Shugart 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 2012-12-30 with Medical categories.


"Applied Computational Genomics" focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics. Dr. Yin Yao Shugart is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland USA. ​



Computational Genetics And Genomics


Computational Genetics And Genomics
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Author : Gary Peltz
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-11-05

Computational Genetics And Genomics written by Gary Peltz 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 2007-11-05 with Medical categories.


Ultimately, the quality of the tools available for genetic analysis and experimental disease models will be assessed on the basis of whether they provide new information that generates novel treatments for human disease. In addition, the time frame in which genetic discoveries impact clinical practice is also an important dimension of how society assesses the results of the significant public financial investment in genetic research. Because of the investment and the increased expectation that new tre- ments will be found for common diseases, allowing decades to pass before basic discoveries are made and translated into new therapies is no longer acceptable. Computational Genetics and Genomics: Tools for Understanding Disease provides an overview and assessment of currently available and developing tools for genetic analysis. It is hoped that these new tools can be used to identify the genetic basis for susceptibility to disease. Although this very broad topic is addressed in many other books and journal articles, Computational Genetics and Genomics: Tools for Understanding Disease focuses on methods used for analyzing mouse genetic models of biomedically - portant traits. This volume aims to demonstrate that commonly used inbred mouse strains can be used to model virtually all human disea- related traits. Importantly, recently developed computational tools will enable the genetic basis for differences in disease-related traits to be rapidly identified using these inbred mouse strains. On average, a decade is required to carry out the development process required to demonstrate that a new disease treatment is beneficial.



Computational Biology And Genome Informatics


Computational Biology And Genome Informatics
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Author : Paul P Wang
language : en
Publisher: World Scientific
Release Date : 2003-02-19

Computational Biology And Genome Informatics written by Paul P Wang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-02-19 with Computers categories.


This book contains articles written by experts on a wide range of topics that are associated with the analysis and management of biological information at the molecular level. It contains chapters on RNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic network modeling, and phyloinformatics.The important work of some representative researchers in bioinformatics is brought together for the first time in one volume. The topic is treated in depth and is related to, where applicable, other emerging technologies such as data mining and visualization. The goal of the book is to introduce readers to the principle techniques of bioinformatics in the hope that they will build on them to make new discoveries of their own.



Computational Genome Analysis An Introduction


Computational Genome Analysis An Introduction
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Author : Deonier
language : en
Publisher:
Release Date : 2007-10-01

Computational Genome Analysis An Introduction written by Deonier and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-01 with categories.




Computational Biology And Bioinformatics


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