@article{oai:kanazawa-u.repo.nii.ac.jp:00010154,
 author = {長尾, 秀実 and 西川, 清 and Purqon, Acep and Sugiyama, Ayumu and Takamatsu, Yuichiro and Nagao, Hidemi and Nishikawa, Kiyoshi},
 issue = {832},
 journal = {AIP Conference Proceedings},
 month = {May},
 note = {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., 金沢大学大学院自然科学研究科計算科学, 金沢大学理学部},
 pages = {574--577},
 title = {A method of classification and recognition of blue copper protein},
 year = {2006}
}