This book is the first to focus on the application of mathematical
networks for analyzing microarray data. This method goes well
beyond the standard clustering methods traditionally used.
From the contents:
* Understanding and Preprocessing Microarray Data
* Clustering of Microarray Data
* Reconstruction of the Yeast Cell Cycle by Partial Correlations of
Higher Order
* Bilayer Verification Algorithm
* Probabilistic Boolean Networks as Models for Gene
Regulation
* Estimating Transcriptional Regulatory Networks by a Bayesian
Network
* Analysis of Therapeutic Compound Effects
* Statistical Methods for Inference of Genetic Networks and
Regulatory Modules
* Identification of Genetic Networks by Structural Equations
* Predicting Functional Modules Using Microarray and Protein
Interaction Data
* Integrating Results from Literature Mining and Microarray
Experiments to Infer Gene Networks
The book is for both, scientists using the technique as well as
those developing new analysis techniques.
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