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Subject: Protein Data Bank (PDB), protein classification, Structural Classification of Proteins (SCOP), Hidden Markov Model (HMM), 3D HMM


Year: 2012


Type: Article



Title: HMM based approach for classifying protein structures


Author: Mirceva, Georgina
Author: Davchev, Dancho



Abstract: To understand the structure-to-function relationship, life sciences researchers and biologists need to retrieve similar structures from protein databases and classify them into the same protein fold. With the technology innovation the number of protein structures increases every day, so, retrieving structurally similar proteins using current structural alignment algorithms may take hours or even days. Therefore, improving the efficiency of protein structure retrieval and classification becomes an important research issue. In this paper we propose novel approach which provides faster classification (minutes) of protein structures. We build separate Hidden Markov Model (HMM) for each class. In our approach we align tertiary structures of proteins. Viterbi algorithm is used to find the most probable path to the model. We have compared our approach against an existing approach named 3D HMM, which also performs alignment of tertiary structures of proteins by using HMM. The results show that our approach is more accurate than 3D HMM.


Publisher:


Relation: International Journal of Bio-Science and Bio-Technology



Identifier: oai:repository.ukim.mk:20.500.12188/22905
Identifier: http://hdl.handle.net/20.500.12188/22905



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HMM based approach for classifying protein structures201213