{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T05:42:43Z","timestamp":1767159763903,"version":"build-2238731810"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"23","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Motivation: So far various statistical and machine learning techniques applied for prediction of \u03b2-turns. The majority of these techniques have been only focused on the prediction of \u03b2-turn location in proteins. We developed a hybrid approach for analysis and prediction of different types of \u03b2-turn.<\/jats:p>\n                  <jats:p>Results: A two-stage hybrid model developed to predict the \u03b2-turn Types I, II, IV and VIII. Multinomial logistic regression was initially used for the first time to select significant parameters in prediction of \u03b2-turn types using a self-consistency test procedure. The extracted parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in \u03b2-turn sequence. The most significant parameters were then selected using multinomial logistic regression model. Among these, the occurrences of glutamine, histidine, glutamic acid and arginine, respectively, in positions i, i + 1, i + 2 and i + 3 of \u03b2-turn sequence had an overall relationship with five \u03b2-turn types. A neural network model was then constructed and fed by the parameters selected by multinomial logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains by 9-fold cross-validation. It has been observed that the hybrid model gives a Matthews correlation coefficient (MCC) of 0.235, 0.473, 0.103 and 0.124, respectively, for \u03b2-turn Types I, II, IV and VIII. Our model also distinguished the different types of \u03b2-turn in the embedded binary logit comparisons which have not carried out so far.<\/jats:p>\n                  <jats:p>Availability: Available on request from the authors.<\/jats:p>\n                  <jats:p>Contact: \u00a0parviz@modares.ac.ir<\/jats:p>","DOI":"10.1093\/bioinformatics\/btm324","type":"journal-article","created":{"date-parts":[[2007,6,28]],"date-time":"2007-06-28T20:25:06Z","timestamp":1183062306000},"page":"3125-3130","source":"Crossref","is-referenced-by-count":14,"title":["Analysis and identification of \u03b2-turn types using multinomial logistic regression and artificial neural network"],"prefix":"10.1093","volume":"23","author":[{"given":"Mehdi","family":"Poursheikhali Asgary","sequence":"first","affiliation":[{"name":"1 Department of Biophysics, Faculty of Basic Sciences and 2Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran"}]},{"given":"Samad","family":"Jahandideh","sequence":"additional","affiliation":[{"name":"1 Department of Biophysics, Faculty of Basic Sciences and 2Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran"}]},{"given":"Parviz","family":"Abdolmaleki","sequence":"additional","affiliation":[{"name":"1 Department of Biophysics, Faculty of Basic Sciences and 2Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran"}]},{"given":"Anoshirvan","family":"Kazemnejad","sequence":"additional","affiliation":[{"name":"1 Department of Biophysics, Faculty of Basic Sciences and 2Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran"}]}],"member":"286","published-online":{"date-parts":[[2007,6,28]]},"reference":[{"key":"2023041107510839200_","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1016\/S0196-9781(03)00133-5","article-title":"Prediction of \u03b2-turns with learning machines","volume":"24","author":"Cai","year":"2003","journal-title":"Peptides"},{"key":"2023041107510839200_","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1006\/abio.2000.4757","article-title":"Prediction of tight turns and their types in proteins","volume":"286","author":"Chou","year":"2000","journal-title":"Anal. 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