RETRACTED: Analysis and identification of β-turn types using multinomial logistic regression and artificial neural network (Retracted Article)

被引:12
|
作者
Asgary, Mehdi Poursheikhali
Jahandideh, Samad
Abdolmaleki, Parviz [1 ]
Kazemnejad, Anoshirvan
机构
[1] Tarbiat Modares Univ, Fac Basic Sci, Dept Biophys, Tehran, Iran
[2] Tarbiat Modares Univ, Fac Med Sci, Dept Biostat, Tehran, Iran
关键词
SECONDARY STRUCTURE; PROTEINS; PREDICTION; LYSOZYME;
D O I
10.1093/bioinformatics/btm324
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: So far various statistical and machine learning techniques applied for prediction of beta-turns. The majority of these techniques have been only focused on the prediction of beta-turn location in proteins. We developed a hybrid approach for analysis and prediction of different types of beta-turn. Results: A two-stage hybrid model developed to predict the beta-turn Types I, II, IV and VIII. Multinomial logistic regression was initially used for the first time to select significant parameters in prediction of beta-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 beta-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 beta-turn sequence had an overall relationship with five beta-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 beta-turn Types I, II, IV and VIII. Our model also distinguished the different types of beta-turn in the embedded binary logit comparisons which have not carried out so far.
引用
收藏
页码:3125 / 3130
页数:6
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