MATEC Web of Conferences
Volume 56, 20162016 8th International Conference on Computer and Automation Engineering (ICCAE 2016)
|Number of page(s)||5|
|Published online||26 April 2016|
Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)
1 Hankuk Academy of Foreign Studies, Student, 17035 Gyeonggi-do Yongin, Korea
2 Hankuk Academy of Foreign Studies, Science and Information Department, 17035 Gyeonggi-do Yongin, Korea
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.
© Owned by the authors, published by EDP Sciences, 2016
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