Series:

Chapman & Hall/CRC Mathematical and Computational Biology

4 total works

Cover of Pathway Analysis of High Throughput Experiments

Microarrays allow researchers to simultaneously monitor the expression of thousands of genes. Independent of the platform and analysis methods used, the result of a microarray experiment is a list of differentially expressed genes. Presenting a unified analysis of the field, this book explores the tools available to better understand the underlying biological phenomena of differentially expressed genes. It focuses on two major analytic approaches: 1) ontological profiling and 2) gene interaction networks and known pathways. The author presents the fundamentals and tools for each approach.

Cover of An Introduction to Statistics and Data Analysis for Bioinformatics Using R

From the very basics to linear models, this book provides a complete introduction to statistics, data analysis, and R for bioinformatics research and applications. It covers ANOVA, cluster analysis, visualization tools, and machine learning techniques. Suitable for self-study and courses in computational biology, bioinformatics, statistics, and the life sciences, the text also presents examples of microarrays and bioinformatics applications. R code illustrates all of the essential concepts and is available on an accompanying CD-ROM.

Cover of Bioinformatics Databases

Bioinformatics Databases

by Sorin Draghici

Published 25 February 2013
Unlike most existing texts that either focus on algorithms or on teaching the user how to navigate through specific existing databases, Bioinformatics Databases: Design, Implementation, and Usage provides comprehensive coverage of all aspects of bioinformatics databases. This book presents database schemas, code, website links to various databases, and sample applications that connect to these databases. Additional topics include genomic databases, database design issues, integration of databases, as well as current data formats and standards. The text also addresses software design issues and offers practical examples of the design and implementation of bioinformatics databases and tools.

Cover of Statistics and Data Analysis for Microarrays Using R and Bioconductor

Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on, example-based approach that teaches students the basics of R and microarray technology as well as how to choose and apply the proper data analysis tool to specific problems.

New to the Second EditionCompletely updated and double the size of its predecessor, this timely second edition replaces the commercial software with the open source R and Bioconductor environments. Fourteen new chapters cover such topics as the basic mechanisms of the cell, reliability and reproducibility issues in DNA microarrays, basic statistics and linear models in R, experiment design, multiple comparisons, quality control, data pre-processing and normalization, Gene Ontology analysis, pathway analysis, and machine learning techniques. Methods are illustrated with toy examples and real data and the R code for all routines is available on an accompanying downloadable resource.

With all the necessary prerequisites included, this best-selling book guides students from very basic notions to advanced analysis techniques in R and Bioconductor. The first half of the text presents an overview of microarrays and the statistical elements that form the building blocks of any data analysis. The second half introduces the techniques most commonly used in the analysis of microarray data.