Soft Computing Methods for Disulfide Connectivity Prediction

Evolutionary Bioinformatics - Tập 11 - 2015
Alfonso E. Márquez Chamorro1, Jesús S. Aguilar–Ruiz1
1School of Engineering, Pablo de Olavide University, Seville, Spain#TAB#

Tóm tắt

The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.

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Evolutionary Bioinformatics

Tập 11

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