Disparate data fusion for protein phosphorylation prediction

DOI10.1007/s10479-008-0347-9zbMath1186.92017OpenAlexW2072644812MaRDI QIDQ970186

Pamela J. Williams, W. Michael Brown, Jean-Loup Faulon, Kenneth L. Sale, Genetha A. Gray

Publication date: 10 May 2010

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://www.osti.gov/biblio/1264179

zbMATH Keywords

ensemble classificationbase classifier

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Computing methodologies and applications (68U99) Biochemistry, molecular biology (92C40) Systems biology, networks (92C42)

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Uses Software

• KinasePhos

Cites Work

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• Bagging predictors
• Stochastic models for heterogeneous DNA sequences
• The weighted majority algorithm
• An empirical study of two approaches to sequence learning for anomaly detection
• Towards a comprehensive collection of diagnostic patterns for protein sequence classification
• Reduced bio basis function neural network for identification of protein phosphorylation sites: comparison with pattern recognition algorithms
• Bayesian and Dempster-Shafer fusion
• Learning representations by back-propagating errors