An information theoretic approach for improving data driven prediction of protein model quality

DOI10.1016/J.CAMWA.2006.12.096zbMath1137.92310OpenAlexW2088685926MaRDI QIDQ929168

Alfonso Montuori, Giovanni Raimondo, Eros Pasero

Publication date: 12 June 2008

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2006.12.096

zbMATH Keywords

relative entropyfeature selectionstatistical learningprotein structure predictionprotein model quality

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40)

Uses Software

• Neural Network Toolbox
• Naccess
• SVM
• MaxSub

Cites Work

• Unnamed Item
• Unnamed Item
• An Algorithm for Least-Squares Estimation of Nonlinear Parameters
• 10.1162/153244303322753616
• On Estimation of a Probability Density Function and Mode

This page was built for publication: An information theoretic approach for improving data driven prediction of protein model quality