Published in

Springer Verlag, Lecture Notes in Computer Science, p. 611-618

DOI: 10.1007/978-3-540-39737-3_76

Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, 2004.

DOI: 10.1109/siu.2004.1338272

Links

Tools

Export citation

Search in Google Scholar

Prediction of Protein Subcellular Localization Based on Primary Sequence Data

Proceedings article published in 2003 by Mert Özarar, Volkan Atalay, Rengül Çetin Atalay ORCID, R. C. Atalay
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

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 multilayer 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 the point of accepted mutations (PAM) substitution matrix. The statistical test results of the system are presented on a four class problem. P2SL achieves slightly higher prediction accuracy than the similar studies.