Bioinformatics with R Cookbook
- نوع فایل : کتاب
- زبان : انگلیسی
- نویسنده : Paurush Praveen Sinha
- چاپ و سال / کشور: 2014
- تعداد صفحه : 300
- شابک / ISBN : 1783283130
Description
Bioinformatics is an interdisciplinary field that develops and improves upon the methods for storing, retrieving, organizing, and analyzing biological data. R is the primary language used for handling most of the data analysis work done in the domain of bioinformatics.
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.
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.
What You Will Learn
Retrieve biological data from within an R environment without hassling web pages
Annotate and enrich your data and convert the identifiers
Find relevant text from PubMed on which to perform text mining
Find phylogenetic relations between species
Infer relations between genomic content and diseases via GWAS
Classify patients based on biological or clinical features
Represent biological data with attractive visualizations, useful for publications and presentations
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.
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.
What You Will Learn
Retrieve biological data from within an R environment without hassling web pages
Annotate and enrich your data and convert the identifiers
Find relevant text from PubMed on which to perform text mining
Find phylogenetic relations between species
Infer relations between genomic content and diseases via GWAS
Classify patients based on biological or clinical features
Represent biological data with attractive visualizations, useful for publications and presentations
