  This work presents a simple artificial neural network which classifies
proteins into two classes from their sequences alone: the membrane protein
class and the non-membrane protein class. This may be important in the
functional assignment and analysis of open reading frames (ORF's) identified in
complete genomes and, especially, those ORF's that correspond to proteins with
unknown function. The network described here has a simple hierarchical
feed-forward topology and a limited number of neurons which makes it very fast.
By using only information contained in 11 protein sequences, the method was
able to identify, with 100% accuracy, all membrane proteins with reliable
topologies collected from several papers in the literature. Applied to a test
set of 995 globular, water-soluble proteins, the neural network classified
falsely 23 of them in the membrane protein class (97.7% of correct assignment).
The method was also applied to the complete SWISS-PROT database with
considerable success and on ORF's of several complete genomes. The neural
network developed was associated with the PRED-TMR algorithm (Pasquier,C.,
Promponas,V.J., Palaios,G.A., Hamodrakas,J.S. and Hamodrakas,S.J., 1999) in a
new application package called PRED-TMR2. A WWW server running the PRED-TMR2
software is available at http://o2.db.uoa.gr/PRED-TMR2
