Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)

Nowaday, the number of known protein structures is significantly less than the number of known amino acid sequences. It is because the regularity of amino acid depend on structure is not clear and the number of thermodynamic conditions are too many. There are some cases that discovering protein stru...

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Main Authors: Jeong Su Yeon, Yoon Tae Seon, Jeong Chae Yoon
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20165604001
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spelling doaj-b78d92968f6f4a10b356f6764349a7c82021-02-02T00:14:47ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01560400110.1051/matecconf/20165604001matecconf_iccae2016_04001Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)Jeong Su Yeon0Yoon Tae Seon1Jeong Chae Yoon2Hankuk Academy of Foreign Studies, StudentHankuk Academy of Foreign Studies, Science and Information DepartmentHankuk Academy of Foreign Studies, StudentNowaday, the number of known protein structures is significantly less than the number of known amino acid sequences. It is because the regularity of amino acid depend on structure is not clear and the number of thermodynamic conditions are too many. There are some cases that discovering protein structure by experiment. However, It needs much time and cost for increasing the number of amino acid sequences, thus, there is less efficiency. So the empirical method which predict theoretically the structure of protein has been developed. We suggest Central-Based Artificial Neural Network as prediction method of protein structure. CebaANN can analyze similarity more detail by making part of center that affect outcome bigger. In experiment we got 85% of prediction probability at E structure, but we got 34% of probability at total.http://dx.doi.org/10.1051/matecconf/20165604001
collection DOAJ
language English
format Article
sources DOAJ
author Jeong Su Yeon
Yoon Tae Seon
Jeong Chae Yoon
spellingShingle Jeong Su Yeon
Yoon Tae Seon
Jeong Chae Yoon
Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)
MATEC Web of Conferences
author_facet Jeong Su Yeon
Yoon Tae Seon
Jeong Chae Yoon
author_sort Jeong Su Yeon
title Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)
title_short Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)
title_full Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)
title_fullStr Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)
title_full_unstemmed Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)
title_sort application of artificial neural network (ann): development of central-based ann (cebaann)
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2016-01-01
description Nowaday, the number of known protein structures is significantly less than the number of known amino acid sequences. It is because the regularity of amino acid depend on structure is not clear and the number of thermodynamic conditions are too many. There are some cases that discovering protein structure by experiment. However, It needs much time and cost for increasing the number of amino acid sequences, thus, there is less efficiency. So the empirical method which predict theoretically the structure of protein has been developed. We suggest Central-Based Artificial Neural Network as prediction method of protein structure. CebaANN can analyze similarity more detail by making part of center that affect outcome bigger. In experiment we got 85% of prediction probability at E structure, but we got 34% of probability at total.
url http://dx.doi.org/10.1051/matecconf/20165604001
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