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Updated: Jun 25, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
Published on: January 26, 2024
Predicting protein subcellular location: exploiting amino acid based sequence of feature spaces and fusion of diverse
Asifullah Khan1, Abdul Majid, Tae-Sun Choi
1Department of Mechatronics, Gwangju Institute of Science and Technology, Buk-Gu, Gwangju, 500-712, Republic of Korea. asifullah@gist.ac.kr
Abstract:
A novel approach CE-Ploc is proposed for predicting protein subcellular locations by exploiting diversity both in feature and decision spaces. The diversity in a sequence of feature spaces is exploited using hydrophobicity and hydrophilicity of amphiphilic pseudo amino acid composition and a specific learning mechanism. Diversity in learning mechanisms is exploited by fusion of classifiers that are based on different learning mechanisms. Significant improvement in prediction performance is observed using jackknife and independent dataset tests.
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