Microarray Analysis In Bioinformatics
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Methods of Microarray Data Analysis V
Author: Patrick McConnell
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-02-24
As studies using microarray technology have evolved, so have the data analysis methods used to analyze these experiments. The CAMDA (Critical Assessment of Microarray Data Analysis) conference was the first to establish a forum for a cross section of researchers to look at a common data set and apply innovative analytical techniques to microarray data. Methods of Microarray Analysis V includes selected papers from CAMDA'04, and focuses on data sets relating to a significant global health issue, malaria. Previous books focused on classification (V. I), pattern recognition (V. II), quality control issues (V. III), and associating array data with a survival endpoint, lung cancer, (V. IV). The contributions come from research fields including statistics, biology, computer science and mathematics. Part of the book is devoted to review papers, which provide a more general look at various analytical approaches. It also presents some background readings for the advanced topics discussed in the CAMDA papers.
Microarray Bioinformatics
Author: Dov Stekel
language: en
Publisher: Cambridge University Press
Release Date: 2003-09-08
This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray experiments. It is written for researchers, clinicians, laboratory heads and managers, from both biology and bioinformatics backgrounds, who work with, or who intend to work with microarrays. The book covers all aspects of microarray bioinformatics, giving you the tools to design arrays and experiments, to analyze your data, and to share your results with your organisation or with the international community. There are chapters covering sequence databases, oligonucleotide design, experimental design, image processing, normalisation, identifying differentially expressed genes, clustering, classification and data standards. The book is based on the highly successful Microarray Bioinformatics course at Oxford University, and therefore is ideally suited for teaching the subject at postgraduate or professional level.
Microarray Gene Expression Data Analysis
This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays