Predicting the Phosphorylation Sites Using Hidden Markov Models and Machine Learning Methods

Abstract

Accurately predicting phosphorylation sites in proteins is an important issue in postgenomics, for which how to efficiently extract the most predictive features from amino acid sequences for modeling is still challenging. Although both the distributed encoding method and the bio-basis function method work well, they still have some limits in use. The… (More)
DOI: 10.1021/ci050047+

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