Literature DB >> 8670618

HTP: a neural network-based method for predicting the topology of helical transmembrane domains in proteins.

P Fariselli1, R Casadio.   

Abstract

In this paper we describe a microcomputer program (HTP) for predicting the location and orientation of alpha-helical transmembrane segments in integral membrane proteins. HTP is a neural network-based tool which gives as output the protein membrane topology based on the statistical propensity of residues to be located in external and internal loops. This method, which uses single protein sequences as input to the network system, correctly predicts the topology of 71 out of 92 membrane proteins of putative membrane orientation, independently of the protein source.

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Year:  1996        PMID: 8670618     DOI: 10.1093/bioinformatics/12.1.41

Source DB:  PubMed          Journal:  Comput Appl Biosci        ISSN: 0266-7061


  4 in total

1.  TMPDB: a database of experimentally-characterized transmembrane topologies.

Authors:  Masami Ikeda; Masafumi Arai; Toshikatsu Okuno; Toshio Shimizu
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

2.  Topology prediction for helical transmembrane proteins at 86% accuracy.

Authors:  B Rost; P Fariselli; R Casadio
Journal:  Protein Sci       Date:  1996-08       Impact factor: 6.725

3.  IgTM: an algorithm to predict transmembrane domains and topology in proteins.

Authors:  Piedachu Peris; Damián López; Marcelino Campos
Journal:  BMC Bioinformatics       Date:  2008-09-10       Impact factor: 3.169

4.  TRAMPLE: the transmembrane protein labelling environment.

Authors:  Piero Fariselli; Michele Finelli; Ivan Rossi; Mauro Amico; Andrea Zauli; Pier Luigi Martelli; Rita Casadio
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

  4 in total

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