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A method of classification and recognition of blue copper protein

フォーマット:
論文
責任表示:
Purqon, Acep ; Sugiyama, Ayumu ; Takamatsu, Yuichiro ; Nagao, Hidemi ; Nishikawa, Kiyoshi
言語:
英語
出版情報:
American Institute of Physics, 2006-05-01
著者名:
掲載情報:
AIP Conference Proceedings
ISSN:
0094-243x  CiNii Research  Webcat Plus  JAIRO
巻:
832
通号:
5
開始ページ:
574
終了ページ:
577
バージョン:
publisher
概要:
金沢大学大学院自然科学研究科計算科学<br />金沢大学理学部<br />Some proteins in blue copper proteins have similar properties. In some cases it is not easy to distinguish the proteins each other. The study to recognize and classify in blue copper proteins has important roles to recognize the difference of similar properties, for examples, structures and residue sequences in blue copper proteins. There are many methods being developed to predict protein structure from many approachs, which one still not satisfactory yet. Therefore it is a challenge for scientists to develop or improve their methods. One of promising method is artificial neural networks (ANN). ANN is learning machine methods consisted of input, hidden and output layer. ANN is tested to recognize secondary structure in blue copper protein. It is found that ANN can distinguish for 7-type of secondary structure and recognize 72% secondary structure in blue copper protein. © 2006 American Institute of Physics. 続きを見る
URL:
http://hdl.handle.net/2297/3451
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