Bioinformatics with R Cookbook


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Bioinformatics with R Cookbook
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Overview
Table of Contents
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Sample Chapters
  • Use the existing R-packages to handle biological data
  • Represent biological data with attractive visualizations
  • An easy-to-follow guide to handle real-life problems in Bioinformatics like Next Generation Sequencing and Microarray Analysis

Book Details

Language : English
Paperback : 300 pages [ 235mm x 191mm ]
Release Date : July 2014
ISBN : 1783283130
ISBN 13 : 9781783283132
Author(s) : Paurush Praveen
Topics and Technologies : All Books, Cookbooks, Open Source
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Paurush Praveen

Paurush Praveen is an engineer by training, and later specialized in Bioinformatics with his Master’s and Ph.D. at the University of Bonn (Germany). He worked with Bioinformatics for six years and R for five years during his research. Working on high-throughput data analysis and modeling, he developed methods and algorithms to solve biological problems (most of them available as or in R packages).

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What you will learn from this book

  • Retrieve biological data from within an R environment without hassling webpages
  • Annotate and enrich your data and convert the identifiers
  • Find relevant text from PubMed on which to perform text mining
  • Perform sequence analyses and alignment
  • Find phylogenetic relations between species
  • Analyze gene expression data
  • Infer relations between genomic content and diseases via GWAS
  • Learn to cluster genes and proteins based on their expression or other features
  • Classify patients based on biological or clinical features
  • Identify biomarkers from biological data using statistical tests
  • Represent biological data with attractive visualizations, useful for publications and presentations

In Detail

Bioinformatics is an interdisciplinary field that develops and improves upon the methods for storing, retrieving, organizing and analyzing biological data. An enormous amount of such data is being generated in life science research today. R is the primary language used for handling most of the data analysis work done in the domain of bioinformatics. A comprehensive illustration on using R for biological and clinical data can be therefore far-reaching.

"Bioinformatics with R Cookbook" is a hands-on guide that provides you with a number of recipes offering you solutions to all the computational tasks related to Bioinformatics in terms of packages and tested codes. Whether you are a bioinformatician or a computational biologist, this book will help you meet the requirements of biological data analysis and modeling in a convenient fashion.

"Bioinformatics with R Cookbook" is a practical book which will help you as a biologist develop computational models and structure biological data with the help of R. The book starts with a high level introduction to R programming. It then goes on to explain the retrieval of data from remote databases, surpassing the barrier of browser-based retrieval. The book then breaks down the mystery of various types of biological data such as gene expression, mass spectrometry, and Next Generation Sequencing. You will then take a look at biological databases, identifier conversion, and enrichment, followed by sequence analysis and structure analysis of biological molecules. Finally, the book moves on to real applications in terms of machine learning, including clustering and classification.

With the help of this book, you will learn how to analyze biological data using R, allowing you to infer new knowledge from your data coming from different types of experiments stretching from microarray to NGS and mass spectrometry.

Approach

This book is an easy-to-follow, stepwise guide to handle real life Bioinformatics problems. Each recipe comes with a detailed explanation to the solution steps. A systematic approach, coupled with lots of illustrations, tips, and tricks will help you as a reader grasp even the trickiest of concepts without difficulty.

Who this book is for

This book is ideal for computational biologists and bioinformaticians with basic knowledge of R programming, bioinformatics and statistics. If you want to understand various critical concepts needed to develop your computational models in Bioinformatics, then this book is for you. Basic knowledge of R is expected.

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