TRANSMEM - A NEURAL-NETWORK IMPLEMENTED IN EXCEL SPREADSHEETS FOR PREDICTING TRANSMEMBRANE DOMAINS OF PROTEINS

Motivation: Genomic sequences from different organisms, even prokaryot ic, have plenty of orphan ORFs, making necessary methods for the predi ction of protein structure and function. The prediction of the presenc e of hydrophobic transmembrane (HTM) stretches is a valuable clue for this. Results: The program, TransMem, based on a neural network and ru nning on personal computers (either Apple Macintosh or PC, using Excel worksheets), for the prediction and distribution of amino acid residu es in transmembrane segments of integral membrane proteins is reported . The percentage of residue predictive accuracy obtained for the set o f proteins tested is 93%, ranging from 99.9% for the best to 71.7% for the worst prediction. The segment-based accuracy is 93.6%; 63.6% of t he protein set match any of the predicted and observed segment locatio ns. Availability: TransMem is available upon request or by anonymous f tp: IP address: luz.uab.es, directory /pub/TransMem. It is also placed on the EMBL file sewer (ftp://ftp.ebi.ac.uk/pub/software/mac/TransMem ).