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.

DOI: 10.1109/IJCNN.2009.5178943

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Cite this paper

@article{Leiva2009FeedforwardAN, title={Feed-forward Artificial Neural Network based inference system applied in bioinformatics data-mining}, author={Mauricio U. Leiva and Tom{\'a}s Arredondo and Diego Candel and Lioubov Dombrovskaia and Loreine Agull{\'o} and Michael Seeger and F{\'e}lix V{\'a}squez}, journal={2009 International Joint Conference on Neural Networks}, year={2009}, pages={1744-1749} }