Due to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics. R Programming for Bioinformatics explores the programming skills needed to use this software tool for the solution of bioinformatics and computational biology problems.

Drawing on the author’s first-hand experiences as an expert in R, the book begins with coverage on the general properties of the R language, several unique programming aspects of R, and object-oriented programming in R. It presents methods for data input and output as well as database interactions. The author also examines different facets of string handling and manipulations, discusses the interfacing of R with other languages, and describes how to write software packages. He concludes with a discussion on the debugging and profiling of R code.

With numerous examples and exercises, this practical guide focuses on developing R programming skills in order to tackle problems encountered in bioinformatics and computational biology.

Contenuti:

Introducing R
Motivation
A note on the text
R Language Fundamentals
Data structures
Managing your R session
Language basics
Subscripting and subsetting
Vectorized computations
Replacement functions
Functional programming
Writing functions
Flow control
Exception handling
Evaluation
Lexical scope
Graphics
Object-Oriented Programming in R
The basics of OOP
S3 OOP
S4 OOP
Using classes and methods in packages
Documentation
Debugging
Managing S3 and S4 together
Navigating the class and method hierarchy
Input and Output in R
Basic file handling
Connections
File input and output
Source and sink: capturing R output
Tools for accessing files on the Internet
Working with Character Data
Built-in capabilities
Regular expressions
Prefixes, suffixes and substrings
Biological sequences
Matching patterns
Foreign Language Interfaces
Calling C and FORTRAN from R
Writing C code to interface with R
Using the R API
Loading libraries
Advanced topics
Other languages
R Packages
Package basics
Package management
Package authoring
Initialization
Data Technologies
Using R for data manipulation
Example
Database technologies
XML
Bioinformatics resources on the WWW
Debugging and Profiling
The browser function
Debugging in R
Debugging C and other foreign code
Profiling R code
Managing memory
References
An Introduction appears at the beginning of each chapter.

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