Feed-forward Artificial Neural Network based inference system applied in bioinformatics data-mining

Abstract

This paper describes a neural network based inference system developed as part of a bioinformatic application in order to help implement a systematic search scheme for the identification of genes which encode enzymes of metabolic pathways. The inference system uses BLAST sequence alignment values as inputs and generates a classification of the best candidates for inclusion in a metabolic pathway map. The system considers a workflow that allows the user to provide feedback with their final classification decisions. These are stored in conjunction with analyzed sequences for re-training and constant inference system improvement.