Abstract
A major challenge in structural bioinformatics is the prediction of protein structure and function from primary amino acid sequences. The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. In this paper, we developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression with parametric insensitive model.
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Hao, PY., Tsai, LB. (2009). Predicting Residue-Wise Contact Orders in Proteins by Support Vector Regression with Parametric-Insensitive Model. In: Chien, BC., Hong, TP. (eds) Opportunities and Challenges for Next-Generation Applied Intelligence. Studies in Computational Intelligence, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92814-0_2
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DOI: https://doi.org/10.1007/978-3-540-92814-0_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92813-3
Online ISBN: 978-3-540-92814-0
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