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- Title
A hierarchical unsupervised growing neural network for clustering gene expression patterns.
- Authors
Herrero, J; Valencia, A; Dopazo, J
- Abstract
We describe a new approach to the analysis of gene expression data coming from DNA array experiments, using an unsupervised neural network. DNA array technologies allow monitoring thousands of genes rapidly and efficiently. One of the interests of these studies is the search for correlated gene expression patterns, and this is usually achieved by clustering them. The Self-Organising Tree Algorithm, (SOTA) (Dopazo,J. and Carazo,J.M. (1997) J. Mol. Evol., 44, 226-233), is a neural network that grows adopting the topology of a binary tree. The result of the algorithm is a hierarchical cluster obtained with the accuracy and robustness of a neural network.
- Publication
Bioinformatics (Oxford, England), 2001, Vol 17, Issue 2, p126
- ISSN
1367-4803
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/17.2.126