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Prediction and classification of protein subcellular location—sequence-order effect and pseudo amino acid composition

✍ Scribed by Kuo-Chen Chou; Yu-Dong Cai

Publisher
John Wiley and Sons
Year
2003
Tongue
English
Weight
206 KB
Volume
90
Category
Article
ISSN
0730-2312

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✦ Synopsis

Given a protein sequence, how to identify its subcellular location? With the rapid increase in newly found protein sequences entering into databanks, the problem has become more and more important because the function of a protein is closely correlated with its localization. To practically deal with the challenge, a dataset has been established that allows the identification performed among the following 14 subcellular locations: (1) cell wall, (2) centriole, (3) chloroplast, (4) cytoplasm, (5) cytoskeleton, (6) endoplasmic reticulum, (7) extracellular, (8) Golgi apparatus, (9) lysosome, (10) mitochondria, (11) nucleus, (12) peroxisome, (13) plasma membrane, and (14) vacuole. Compared with the datasets constructed by the previous investigators, the current one represents the largest in the scope of localizations covered, and hence many proteins which were totally out of picture in the previous treatments, can now be investigated. Meanwhile, to enhance the potential and flexibility in taking into account the sequence-order effect, the series-mode pseudo-amino-acid-composition has been introduced as a representation for a protein. High success rates are obtained by the re-substitution test, jackknife test, and independent dataset test, respectively. It is anticipated that the current automated method can be developed to a high throughput tool for practical usage in both basic research and pharmaceutical industry.

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