2014/09/02 by Rezaul Karim, Karim, Rezaul, Mohd. Momin Al Aziz +11
Biochemistry, Genetics and Molecular Biology · Computer Science · #Computational Engineering #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Finance #Genetics, Bioinformatics, and Biomedical Research #Information Retrieval (cs.IR) #Machine Learning in Bioinformatics #Protein Structure and Dynamics #and Science (cs.CE) #cs.CE #cs.CV #cs.IR
paper · pdf · doi:10.48550/arxiv.1409.0814
draft
arxiv created 2014/09/02 · openalex publication_date 2014/09/02 · arxiv updated 2014/09/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Due to the advancements in technology number of entries in the structural database of proteins are increasing day by day. Methods for retrieving protein tertiary structures from this large database is the key to comparative analysis of structures which plays an important role to understand proteins and their function. In this paper, we present fast and accurate methods for the retrieval of proteins from a large database with tertiary structures similar to a query protein. Our proposed methods borrow ideas from the field of computer vision. The speed and accuracy of our methods comes from the two newly introduced features, the co-occurrence matrix of the oriented gradient and pyramid histogram of oriented gradient and from the use of Euclidean distance as the distance measure. Experimental results clearly indicate the superiority of our approach in both running time and accuracy. Our method is readily available for use from this website: http://research.buet.ac.bd:8080/Comograd/.