swMATH ID: 35378
Software Authors: Ahmet Sacan, Ozgur Ozturk, Hakan Ferhatosmanoglu, Yusu Wang
Description: LFM-Pro: a tool for detecting significant local structural sites in proteins. Results: We propose Local Feature Mining in Proteins (LFM-Pro) as a framework for automatically discovering family-specific local sites and the features associated with these sites. Our method uses the distance field to backbone atoms to detect geometrically significant structural centers of the protein. A feature vector is generated from the geometrical and biochemical environment around these centers. These features are then scored using a statistical measure, for their ability to distinguish a family of proteins from a background set of unrelated proteins, and successful features are combined into a representative set for the protein family. The utility and success of LFM-Pro are demonstrated on trypsin-like serine proteases family of proteins and on a challenging classification dataset via comparison with DALI. The results verify that our method is successful both in identifying the distinctive sites of a given family of proteins, and in classifying proteins using the extracted features. Availability: The software and the datasets are freely available for academic research use at http://bioinfo.ceng.metu.edu.tr/Pub/LFMPro
Homepage: https://academic.oup.com/bioinformatics/article/23/6/709/417999
Related Software: SPatt; SVM-Prot; MotifCut; PRED-CLASS; BLAST; PSI-BLAST; GOtcha; SVMlight
Cited in: 2 Publications

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