Abstract
This work proposes an improvement of the multi-objective evolutionary method for the protein residue-residue contact prediction called MECoMaP. This method bases its prediction on physico-chemical properties of amino acids, structural features and evolutionary information of the proteins. The evolutionary algorithm produces a set of decision rules that identifies contacts between amino acids. These decision rules generated by the algorithm represent a set of conditions to predict residue-residue contacts. A new encoding used, a fast evaluation of the examples from the training data set and a treatment of unbalanced classes of data were considered to improve the the efficiency of the algorithm.
Chapter PDF
Similar content being viewed by others
Keywords
References
Tegge, A., Wang, Z., Eickholt, J., Cheng, J.: Nncon: Improved protein contact map prediction using 2d-recursive neural networks. Nucleic Acids Research 37(2), 515–518 (2009)
Jones, D.T., Buchan, D.W., Cozzetto, D., Pontil, M.: Psicov: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments. Bioinformatics 28(2), 184–190 (2012)
Calvo, J.C., Ortega, J.: Parallel protein structure prediction by multiobjective optimization. Parallel, Distributed and Network-based Processing 12(4), 407–413 (2009)
Marquez-Chamorro, A.E., Asencio, G., Divina, F., Aguilar-Ruiz, J.S.: Evolutionary decision rules for predicting protein contact maps. Pattern Analysis and Applications, PAAA (September 1-13, 2012)
Russell, R.B., Betts, M.J., Barnes, M.R.: Amino acid properties and consequences of subsitutions. In: Bioinformatics for Geneticists. Wiley (2003)
Fariselli, P., Olmea, O., Valencia, A., Casadio, R.: Prediction of contact map with neural networks and correlated mutations. Protein Engineering 14, 133–154 (2001)
Cheng, J., Baldi, P.: Improved residue contact prediction using support vector machines and a large feature set. Bioinformatics 8, 113 (2007)
Gupta, N., Mangal, N., Biswas, S.: Evolution and similarity evaluation of protein structures in contact map space. Proteins: Structure, Function, and Bioinformatics 59, 196–204 (2005)
Kyte, J., Doolittle, R.F.: A simple method for displaying the hydropathic character of a protein. J. J. Mol. Bio. 157, 105–132 (1982)
Grantham, R.: Amino acid difference formula to help explain protein evolution. J. J. Mol. Bio. 185, 862–864 (1974)
Klein, P., Kanehisa, M., DeLisi, C.: Prediction of protein function from sequence properties: Discriminant analysis of a data base. Bioch. Bioph. 787, 221–226 (1984)
Adelson-Velskii, G., Landis, E.M.: An algorithm for the organization of information. Proceedings of the USSR Academy of Sciences; Soviet Math. 3, 1259–1263
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.: The weka data mining software: An update. SIGKDD Explorations 11 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Márquez Chamorro, A.E., Divina, F., Aguilar-Ruiz, J.S., Santiesteban Toca, C.E. (2013). Improving the Efficiency of MECoMaP: A Protein Residue-Residue Contact Predictor. In: Ruiz-Shulcloper, J., Sanniti di Baja, G. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2013. Lecture Notes in Computer Science, vol 8259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41827-3_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-41827-3_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41826-6
Online ISBN: 978-3-642-41827-3
eBook Packages: Computer ScienceComputer Science (R0)