Analysis and identification of β-turn types using multinomial logistic regression and artificial neural network | Zendy

Mehdi Poursheikhali Asghari | Zendy; Samad Jahandideh | Zendy; Parviz Abdolmaleki | Zendy; Anoshirvan Kazemnejad | Zendy

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Analysis and identification of β-turn types using multinomial logistic regression and artificial neural network

Author(s) -

Mehdi Poursheikhali Asghari,

Samad Jahandideh,

Parviz Abdolmaleki,

Anoshirvan Kazemnejad

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm324

Subject(s) - multinomial logistic regression , artificial neural network , identification (biology) , logistic regression , computer science , multinomial distribution , artificial intelligence , machine learning , pattern recognition (psychology) , statistics , mathematics , biology , botany

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.

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