Fuzzy classification of secretory signals in proteins encoded by the plasmodium falciparum genome

Abstract

Over five thousand types of protein are produced by the malaria parasite Plasmodiumfalcipariun. Each protein contains the address of a specific destination to which it will be trafficked by various cellular translocation mechanisms. This address may be encoded in a secretory signal, physically represented as an amino acid subsequence forming a motif or pattern. The different signal sequences are classified according to where they occur with respect to the entire amino acid sequence. Biologists are interested in computational techniques that can automatically classify the large amount of data in the Plasmodium falciparun genome, since they have inferred from ongoing experimentation that a correlation exists between particular signals and significant cellular locations. We describe the development of a web-accessible fuzzy classifier of secretory signals in proteins. The application of this classifier to the entire P. falcipariim genome immediately produced some biologically-interesting predictions that are briefly discussed. © Springer-Verlag 2004.