Prediction of plasma membrane spanning region and topology using hidden markov model and neural network

Min Kyung Kim, Hyun Seok Park, Seon Hee Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Unlike bacteria, which generally consist of a single intracellular compartment surrounded by a plasma membrane, a eukaryotic cell is elaborately subdivided into functionally distinct, membrane-enclosed intracellular compartments that are composed of the nucleus, mitochondria, and chloroplast. Although transmembrane spanning region and topology prediction tools are available, such software cannot distinguish plasma membrane from intracellular membrane. Moreover, the presence of signal peptide, which has information of intracellular targeting, complicates the transmembrane topology prediction because the hydrophobic composite of signal peptide is considered to be a putative transmembrane region. By immediately detecting a signal peptide and transmembrane topology in a query sequence, we can discriminate plasma membrane spanning proteins from intracellular membrane spanning proteins. Moreover, the prediction performance significantly increases when signal peptide is contained in queries. Transmembrane region prediction algorithm based on the Hidden Markov Model and ER signal peptide detection architecture for neural networks has been used for the actual implementation of the software.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
PublisherSpringer Verlag
Pages270-277
Number of pages8
ISBN (Print)9783540232056
DOIs
StatePublished - 2004
Event8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004 - Wellington, New Zealand
Duration: 20 Sep 200425 Sep 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3215
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004
Country/TerritoryNew Zealand
CityWellington
Period20/09/0425/09/04

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