Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. Our HMM based approach
  2.1. Hidden Markov Model (HMM)
  2.2. Efficient representation of protein structures
 3. Experimental results
 4. Conclusion
 References

키워드

저자

• Georgina Mirceva [ Faculty of Electrical Engineering and Information Technologies University Ss. Cyril and Methodius, Skopje, Macedonia ]
• Danco Davcev [ Faculty of Electrical Engineering and Information Technologies University Ss. Cyril and Methodius, Skopje, Macedonia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605