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

✍ Scribed by Alfonso Montuori; Giovanni Raimondo; Eros Pasero

Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
778 KB
Volume
55
Category
Article
ISSN
0898-1221

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✦ Synopsis

We present the results of an information theory-based approach to select an optimal subset of features for the prediction of protein model quality. The optimal subset of features was calculated by means of a backward selection procedure. The performances of a probabilistic classifier modeled by means of a Kernel Probability Density Estimation method (KPDE) were compared with those of a feed-forward Artificial Neural Network (ANN) and a Support Vector Machine (SVM).

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