Predicting the secondary structure of proteins using Machine Learning algorithms

Rui Camacho, Ana Rita Ferreira, Natacha Rosa, Vânia Guimarães, Nuno A. Fonseca, Vítor Santos Costa, Miguel de Sousa and Alexandre L. Magalhães

2012

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Abstract

The functions of proteins in living organisms are related to their 3-D structure, which is known to be ultimately determined by their linear sequence of amino acids that together form these macromolecules. It is, therefore, of great importance to be able to understand and predict how the protein 3D-structure arises from a particular linear sequence of amino acids. In this paper we report the application of Machine Learning methods to predict, with high values of accuracy, the secondary structure of proteins, namely α-helices and β-sheets, which are intermediate levels of the local structure.

Bibtex

@Article{camacho-ijdmb11,
   author =    {R. Camacho, A. R. Ferreira, N. Rosa, V. Guimarães, Nuno A. Fonseca, 
                V. Santos Costa, M. de Sousa and A. L. Magalhães},
   title =     {{Predicting the secondary structure of proteins using Machine Learning algorithms}},
   journal =   {International Journal of Data Mining and Bioinformatics},
   pages =     {571--584},
   volume =    {6},
   year =      {2012},
}

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