Predicting Protein Secondary Structure Using Artificial Neural Networks

Authors

Abstract

This tutorial explains how artificial neural networks can be used to predict protein secondary structure. It begins by describing the constitution and structure of proteins, and some notions about homology and alignments. Then it addresses the reasons for predicting secondary structure, and lists some important prediction methods, followed by a description of our neural network prediction system. It also explains how the results obtained can become more informative and reliable, and finally it contains some considerations regarding the difficulties of predicting protein secondary structure.

Keywords

neural networks, protein secondary structure

Subject

Neural Networks, Application

TechReport Number

05/01

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