Protein disorder prediction by condensed PSSM considering propensity for order or disorder

Background: More and more disordered regions have been discovered in protein sequences, and many of them are found to be functionally significant. Previous studies reveal that disordered regions of a protein can be predicted by its primary structure, the amino acid sequence. One observation that has been widely accepted is that ordered regions usually have compositional bias toward hydrophobic amino acids, and disordered regions are toward charged amino acids. Recent studies further show that employing evolutionary information such as position specific scoring matrices (PSSMs) improves the prediction accuracy of protein disorder. As more and more machine learning techniques have been introduced to protein disorder detection, extracting more useful features with biological insights attracts more attention. Results: This paper first studies the effect of a condensed position specific scoring matrix with respect to physicochemical properties (PSSMP) on the prediction accuracy, where the ...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Chung-Tsai Su, Chien-Yu Chen, Yu-Yen Ou
• Keywords: Amino Acids, BMCBI 2006, Prediction Accuracy, Protein