Mapping Genes to Pathways Using Ontological Fuzzy Rule Systems
In this paper we present a novel algorithm for mapping genes to pathways. The approach is based on the concept of ontological fuzzy rule system (OFRS) that, we believe, represents a step closer toward Zadeh's "computing with words" paradigm. An OFRS is a fuzzy rule system that uses ontological mapping between objects according to their representation as sets of terms from an ontology. In our mapping approach the left-hand-side contains genes objects represented using the gene ontology (GO), and the right-hand-side consists in pathways described using a pathway ontology (KEGG). The question of mapping a set of genes to pathways often arises in microarray experiments where one would like to know what are the pathways that can explain the observed gene expression patterns. To compare various mapping approaches, we use a pilot dataset extracted from KEGG that consisted of 10 sets of 15 genes taken from 3 pathways (5 gene/pathway). We conclude that the best matching strategy consists in two steps: in the first step the crisp approach is used to find the pathways involved, and in the second step the fuzzy (ontological) approach is employed to map the genes that could not be found in KEGG.