Clustering techniques for protein surfaces
Pattern Recognition
A robust medical image segmentation method using KL distance and local neighborhood information
Computers in Biology and Medicine
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A preprocessing algorithm is presented, integrating the computation of biomolecular surfaces, the calculation of geometrical and chemical features on each surface point, and a complex segmentation into characteristic surface regions. Calculated regions cover the whole computed protein surface and are a feature of shape, roughness and hydrophobicity on the appropriate surface area. Such regions can be paired in complementary parts, used to predict possible docking sites of proteins. The segmentation algorithm of docking sites proceeds in two steps: first, surface points are classified with a vector quantizer. Second, connected areas of surface points are computed by a complex region growing technique. The detected regions were compared to the real docking sites calculated from complexes with known 3D structures with good results of approximation.