Prediction of protein subcellular localization based on primary sequence data
Author
Özarar, M.
Atalay, V.
Çetin-Atalay, Rengül
Date
2004Source Title
Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004
Publisher
IEEE
Pages
118 - 120
Language
Turkish
Type
Conference PaperItem Usage Stats
135
views
views
89
downloads
downloads
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.
Keywords
Encoding schemeFour 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