Prediction of protein subcellular localization based on primary sequence data

Date
2004
Advisor
Instructor
Source Title
Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
118 - 120
Language
Turkish
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
Abstract

Subcellular localization is crucial for determining the functions of proteins. A system called prediction of protein subcellular localization (P2SL) that predicts the subcellular localization of proteins in eukaryotic organisms based on the amino acid content of primary sequences using amino acid order is designed. The approach for prediction is to find the most frequent motifs for each protein in a given class based on clustering via self organizing maps and then to use these most frequent motifs as features for classification by the help of multi layer perceptrons. This approach allows a classification independent of the length of the sequence. In addition to these, the use of a new encoding scheme is described for the amino acids that conserves biological function based on point of accepted mutations (PAM) substitution matrix. The statistical test results of the system is presented on a four class problem. P2SL achieves slightly higher prediction accuracy than the similar studies.

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Book Title
Keywords
Encoding scheme, Four class problem, Protein subcellular localization (P2SL), Substitution matrix, Amino acids, Cells, Data reduction, Matrix algebra, Problem solving, Self organizing maps, Signal encoding, Statistical methods, Proteins
Citation
Published Version (Please cite this version)