A technique based on neural network for predicting the secondary structure of proteins

Published

Conference Paper

This paper presents a neural network approach for predicting the secondary structure of proteins from amino acid sequences. We have assumed a simple neural network with one input & output layer. Single hidden layer is also considered. Our neural network can be trained to predict the secondary structure of proteins by studying proteins with already known secondary structure by modifying the weight matrix function. Like other existing methods, our method is also an approximation method and its accuracy depends on the careful study and training of network. The significance of the method is its simplicity and applicability. © 2007 IEEE.

Full Text

Duke Authors

Cited Authors

  • Agarwal, P; Rizvi, SAM

Published Date

  • March 31, 2008

Published In

  • Proceedings International Conference on Computational Intelligence and Multimedia Applications, Iccima 2007

Volume / Issue

  • 2 /

Start / End Page

  • 382 - 386

International Standard Book Number 10 (ISBN-10)

  • 0769530508

International Standard Book Number 13 (ISBN-13)

  • 9780769530505

Digital Object Identifier (DOI)

  • 10.1109/ICCIMA.2007.47

Citation Source

  • Scopus