A System for Predicting Subcellular Localization of Yeast Genome Using Neural Network

Thumbnail Image

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

The subcellular location of a protein can provide valuable information about its function. With the rapid increase of sequenced genomic data, the need for an automated and accurate tool to predict subcellular localization becomes increasingly important. Many efforts have been made to predict protein subcellular localization. This paper aims to merge the artificial neural networks and bioinformatics to predict the location of protein in yeast genome. We introduce a new subcellular prediction method based on a backpropagation neural network. The results show that the prediction within an error limit of 5 to 10 percentage can be achieved with the system.

Keywords

Neural and Evolutionary Computing, Artificial Intelligence

Citation

URI

http://salesiana.dossiersoluciones.com/handle/123456789/139837

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0710.2227
 http://arxiv.org/abs/0710.2227

Collections

arXiv