A segmental semi Markov model for protein secondary structure prediction

DOI10.1016/J.MBS.2009.07.004zbMath1175.92015OpenAlexW2093502662WikidataQ51806965 ScholiaQ51806965MaRDI QIDQ1038262

Seyed Amir Malekpour, Hamid Pezeshk, Changiz Eslahchi, Mehdi Sadeghi, Sima Naghizadeh

Publication date: 17 November 2009

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mbs.2009.07.004

zbMATH Keywords

predictionHMMMarkov modelssegmentationBayesian methodssecondary structureleft-to-right and right-to-left dependencies

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Biochemistry, molecular biology (92C40) Markov processes (60J99)

Related Items (2)

Population-based incremental learning for the prediction of Homo sapiens’ protein secondary structure ⋮ Sonication-induced unfolding proteins

Cites Work

• Biological Sequence Analysis
• Unnamed Item

This page was built for publication: A segmental semi Markov model for protein secondary structure prediction