PMID: 9183525Jun 1, 1997Paper

'TransMem': a neural network implemented in Excel spreadsheets for predicting transmembrane domains of proteins

Computer Applications in the Biosciences : CABIOS
P AloyEnrique Querol

Abstract

Genomic sequences from different organisms, even prokaryotic, have plenty of orphan ORFs, making necessary methods for the prediction of protein structure and function. The prediction of the presence of hydrophobic transmembrane (HTM) stretches is a valuable clue for this. The program. TransMem, based on a neural network and running on personal computers (either Apple Macintosh or PC, using Excel worksheets), for the prediction and distribution of amino acid residues in transmembrane segments of integral membrane proteins is reported. The percentage of residue predictive accuracy obtained for the set of 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 the protein set match any of the predicted and observed segment locations. TransMem is available upon request or by anonymous up: IP address: luz.uab.es, directory/pub/ TransMem. It is also placed on the EMBL file server (ftp:/(/)ftp.ebi.ac.uk/pub/software/mac/TransMem ).

Citations

Nov 27, 1998·Progress in Biophysics and Molecular Biology·G Schneider, P Wrede
May 28, 2003·DNA Repair·Vernon CastilloJordi Surrallés
Mar 25, 2010·BMC Microbiology·David GoudenègeFrédérique Barloy-Hubler
Dec 19, 2003·Nucleic Acids Research·Antoni HermosoEnrique Querol
Dec 19, 2006·Biochemical and Biophysical Research Communications·Xiao-Guang YangZhi-Ping Feng
Jun 30, 2004·Journal of Molecular Biology·Jannick Dyrløv BendtsenSøren Brunak
Mar 26, 1998·Journal of Molecular Biology·M A AndradeB Rost
Dec 27, 2006·Journal of Theoretical Biology·Ying-Li Chen, Qian-Zhong Li
Jun 30, 2006·Journal of Theoretical Biology·Shuang-Quan WangKuo-Chen Chou

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