Protein classification by matching and clustering surface graphs

作     者：Lozano, MA Escolano, F 

作者机构：Univ Alicante Dept Ciencia Computac & Inteligencia Artificial E-03080 Alicante Spain 

出 版 物：《PATTERN RECOGNITION》 (图形识别)

年 卷 期：2006年第39卷第4期

页      面：539-551页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：protein classification graph matching energy minimization graph clustering EM algorithms 

摘      要：In this paper, we address the problem of comparing and classifying protein surfaces with graph-based methods. Comparison relies on matching surface graphs, extracted from the surfaces by considering concave and convex patches, through a kernelized version of the Softassign graph-matching algorithm. On the other hand, classification is performed by clustering the surface graphs with ail EM-like algorithm, also relying on kernelized Softassign, and then calculating the distance of an input surface graph to the closest prototype. We present experiments showing the Suitability of kernelized Softassign for both comparing and classifying surface graphs. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.