Protein secondary structure prediction based on quintuplets

2003/07/16 by Wei‐Mou Zheng, Wei-Mou Zheng, Zheng, Wei-Mou · 1 citation
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · #Biological Physics (physics.bio-ph) #Biomolecules (q-bio.BM) #Data Analysis #FOS: Biological sciences #FOS: Physical sciences #Machine Learning in Bioinformatics #Protein Structure and Dynamics #RNA and protein synthesis mechanisms #Statistics and Probability (physics.data-an) #physics.bio-ph #physics.data-an #q-bio.BM

paper · pdf · doi:10.48550/arxiv.physics/0307076

10 pages with 6 tables

arxiv created 2003/07/16 · openalex publication_date 2003/07/16 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Simple hidden Markov models are proposed for predicting secondary structure of a protein from its amino acid sequence. Since the length of protein conformation segments varies in a narrow range, we ignore the duration effect of length distribution, and focus on inclusion of short range correlations of residues and of conformation states in the models. Conformation-independent and -dependent amino acid coarse-graining schemes are designed for the models by means of proper mutual information. We compare models of different level of complexity, and establish a practical model with a high prediction accuracy.

Citations

• Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features
• A tutorial on hidden Markov models and selected applications in speech recognition

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