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.
Edition
1st ed. Softcover of orig. ed. 2007
Language
Place of publication
Target group
Professional and scholarly
Research
Illustrations
115 s/w Abbildungen
XIV, 176 p. 115 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
ISBN-13
978-1-4419-4179-4 (9781441941794)
DOI
10.1007/978-0-387-34569-7
Schweitzer Classification
Data Mining of Malaria Parasite Gene Expression for Possible Translational Research.- Constructing Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals of the Intraerythrocytic Development Cycle.- Simple Methods for Peak and Valley Detection in Time Series Microarray Data.- Oxidative Stress Genes in Plasmodium falciparum as Indicated by Temporal Gene Expression.- Identifying Stage-Specific Genes by Combining Information from Two Different Types of Oligonucleotide Arrays.- Construction of Malaria Gene Expression Network Using Partial Correlations.- Detecting Network Motifs in Gene Co-expression Networks Through Integration of Protein Domain Information.- Chromosomal Clustering of Periodically Expressed Genes in Plasmodium falciparum.- PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum.- Linking Gene Expression Patterns and Transcriptional Regulation in Plasmodium falciparum.- Chromosomal Spatial Correlation of Gene Expression in Plasmodium falciparum.
