Prediction of protein structural class using novel evolutionary collocation-based sequence representation

: Knowledge of structural classes is useful in understanding of folding patterns in proteins. Although existing structural class prediction methods applied virtually all state-of-the-art classifiers, many of them use a relatively simple protein sequence representation that often includes amino acid (AA) composition. To this end, we propose a novel sequence representation that incorporates evolutionary information encoded using PSI-BLAST profilebased collocation of AA pairs. We used six benchmark datasets and five representative classifiers to quantify and compare the quality of the structural class prediction with the proposed representation. The best, classifier support vector machine achieved 61

• Type: Journal
• Year: 2008
• Where: JCC
• Authors: Ke Chen 0003, Lukasz A. Kurgan, Jishou Ruan
• Keywords: JCC 2008, Sequence Representation, Structural Class Prediction, Structural Classes