Prediction of the subcellular location of prokaryotic proteins based on a new representation of the amino acid composition.

Abstract:

:A new representation of protein sequence is devoted in this paper, in which each protein can be represented by a 20-dimensional (20D) vector of unit length. Inspired by the principle of superposition of state in quantum mechanics, the squares of the 20 components of the vector correspond to the amino acid composition. Using the new representation of the primary sequence and Bayes Discriminant Algorithm, the subcellular location of prokaryotic proteins was predicted. The overall predictive accuracy in the jackknife test can be 3% higher than the result of using amino acid composition directly for the database of sequence identity is less than 90%, but 5% higher when sequence identity is less than 80%. The higher predictive accuracy indicates that the current measure of extracting the information from the primary sequence is efficient. Since the subcellular location restricting a protein's possible function, the present method should also be a useful measure for the systematic analysis of genome data. The program used in this paper is available on request.

journal_name

Biopolymers

journal_title

Biopolymers

authors

Feng ZP

doi

10.1002/1097-0282(20010415)58:5<491::AID-BIP1024>3

subject

Has Abstract

pub_date

2001-04-15 00:00:00

pages

491-9

issue

5

eissn

0006-3525

issn

1097-0282

pii

10.1002/1097-0282(20010415)58:5<491::AID-BIP1024>3

journal_volume

58

pub_type

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