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Updated: Aug 16, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
Prediction of protein subcellular locations using a new measure of information discrepancy
Lixia Jin1, Huanwen Tang, Weiwu Fang
1Bioinformatics and Computational Biology, Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50010, USA. lixiajin@iastate.edu
Abstract:
Given a raw protein sequence, knowing its subcellular location is an important step toward understanding its function and designing further experiments. A novel method is proposed for the prediction of protein subcellular locations from sequences. For four categories of eukaryotic proteins the overall predictive accuracy is 82.0%, 2.6% higher than that by using SVM approach. For three subcellular locations of prokaryotic proteins, an overall accuracy of 89.9% is obtained. In accordance with the architecture of cells, a hierarchical prediction approach is designed. Based on amino acid composition extracellular proteins and intracellular proteins can be identified with accuracy of 97%.
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