{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:09:16Z","timestamp":1777702156477,"version":"3.51.4"},"reference-count":0,"publisher":"SAGE Publications","issue":"1-2","license":[{"start":{"date-parts":[[2009,2,1]],"date-time":"2009-02-01T00:00:00Z","timestamp":1233446400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2009,2]]},"abstract":"<jats:p>The paper provides an alternative approach to protein structural\n\t\t\t class prediction employing artificial neural network. Existing works on protein\n\t\t\t structural class prediction are computationally intensive. The method employs\n\t\t\t SOFM for extraction of representative feature vectors, for the four different\n\t\t\t structural classes and then uses Principal Component Analysis for finding\n\t\t\t optimum feature vector dimension. Nearest neighborhood classification technique\n\t\t\t is finally utilised; to classify these protein datapoints to their respective\n\t\t\t classes. The proposed work presented in this paper, maintains the same level of\n\t\t\t classification accuracy in minimum computation time, as it employs most\n\t\t\t prominent and reduced number of feature set for classification.<\/jats:p>","DOI":"10.3233\/ifs-2009-0415","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T17:40:00Z","timestamp":1575308400000},"page":"61-71","source":"Crossref","is-referenced-by-count":8,"title":["A neural network based approach for protein structural class\t\t\t prediction"],"prefix":"10.1177","volume":"20","author":[{"given":"Ayan","family":"Datta","sequence":"first","affiliation":[{"name":"Dept. of Electronics and Telecommunication\r\t\t\t Engineering, Jadavpur University, Kolkata 700032, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Veera","family":"Talukdar","sequence":"additional","affiliation":[{"name":"Indian Institute of Social Welfare and Buisness,\r\t\t\t Management,College Square West, Kolkata-700073, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amit","family":"Konar","sequence":"additional","affiliation":[{"name":"Dept. of Electronics and Telecommunication\r\t\t\t Engineering, Jadavpur University, Kolkata 700032, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lakhmi C.","family":"Jain","sequence":"additional","affiliation":[{"name":"Knowledge-Based Intelligent Engineering Systems\r\t\t\t Centre, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095,\r\t\t\t Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2009,2]]},"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-2009-0415","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-2009-0415","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:35:03Z","timestamp":1777455303000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-2009-0415"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,2]]},"references-count":0,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2009,2]]}},"alternative-id":["10.3233\/IFS-2009-0415"],"URL":"https:\/\/doi.org\/10.3233\/ifs-2009-0415","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,2]]}}}