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Introduction to Bioinformatics with R - A Practical Guide for Biologists (Paperback)
Loot Price: R1,684
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Introduction to Bioinformatics with R - A Practical Guide for Biologists (Paperback)
Series: Chapman & Hall/CRC Computational Biology Series
Expected to ship within 12 - 17 working days
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In biological research, the amount of data available to researchers
has increased so much over recent years, it is becoming
increasingly difficult to understand the current state of the art
without some experience and understanding of data analytics and
bioinformatics. An Introduction to Bioinformatics with R: A
Practical Guide for Biologists leads the reader through the basics
of computational analysis of data encountered in modern biological
research. With no previous experience with statistics or
programming required, readers will develop the ability to plan
suitable analyses of biological datasets, and to use the R
programming environment to perform these analyses. This is achieved
through a series of case studies using R to answer research
questions using molecular biology datasets. Broadly applicable
statistical methods are explained, including linear and rank-based
correlation, distance metrics and hierarchical clustering,
hypothesis testing using linear regression, proportional hazards
regression for survival data, and principal component analysis.
These methods are then applied as appropriate throughout the case
studies, illustrating how they can be used to answer research
questions. Key Features: * Provides a practical course in
computational data analysis suitable for students or researchers
with no previous exposure to computer programming. * Describes in
detail the theoretical basis for statistical analysis techniques
used throughout the textbook, from basic principles * Presents
walk-throughs of data analysis tasks using R and example datasets.
All R commands are presented and explained in order to enable the
reader to carry out these tasks themselves. * Uses outputs from a
large range of molecular biology platforms including DNA
methylation and genotyping microarrays; RNA-seq, genome sequencing,
ChIP-seq and bisulphite sequencing; and high-throughput phenotypic
screens. * Gives worked-out examples geared towards problems
encountered in cancer research, which can also be applied across
many areas of molecular biology and medical research. This book has
been developed over years of training biological scientists and
clinicians to analyse the large datasets available in their cancer
research projects. It is appropriate for use as a textbook or as a
practical book for biological scientists looking to gain
bioinformatics skills.
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