Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)

Research on Protein Structure Prediction Based on Sequence Pattern

Authors
Juanjuan Yin, Guojian Cheng, Fenggang Ma
Corresponding Author
Juanjuan Yin
Available Online March 2018.
DOI
10.2991/jiaet-18.2018.56How to use a DOI?
Keywords
Protein structure prediction; Hydrophobicity; Apriori all algorithm; KMP pattern matching
Abstract

In order to find meaningful data for human beings in a large number of biological information and then reveal the nature of life, this paper focuses on analyzing the characteristics of the hydrophobicity of amino acids and adjacent information, using sequential pattern mining Apriori All algorithm to extract amino acid sequences, using KMP pattern matching query algorithm to predict amino acid sequences, and then obtaining the secondary structure of protein. The prediction results have high reliability.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)
Series
Advances in Engineering Research
Publication Date
March 2018
ISBN
10.2991/jiaet-18.2018.56
ISSN
2352-5401
DOI
10.2991/jiaet-18.2018.56How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Juanjuan Yin
AU  - Guojian Cheng
AU  - Fenggang Ma
PY  - 2018/03
DA  - 2018/03
TI  - Research on Protein Structure Prediction Based on Sequence Pattern
BT  - Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)
PB  - Atlantis Press
SP  - 318
EP  - 322
SN  - 2352-5401
UR  - https://doi.org/10.2991/jiaet-18.2018.56
DO  - 10.2991/jiaet-18.2018.56
ID  - Yin2018/03
ER  -