A Systems Biology approach for the classification of DNA Microarray Data

In this paper we present a binary graph classifier (BGC) which allows to classify large, unweighted, undirected graphs. The main idea of this classifier is to decompose a graph locally in generalized trees forming the tree set of a graph and to compare the tree sets of graphs by a generalized tree-similarity algorithm (GTSA). We apply our BGC to networks representing co-expressed genes from DNA microarray experiments of cervical cancer and demonstrate, that different tumor stages of the disease can be distinguished on this level of description.

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