SNP-Schizo: a web tool for schizophrenia SNP sequence classification

Authors:
Vanessa Aguiar-Pulido;José A. Seoane;Cristian R. Munteanu;Alejandro Pazos
Affiliations:
Information and Communication Technologies Department, Faculty of Informatics, University of A Coruña, Spain;Information and Communication Technologies Department, Faculty of Informatics, University of A Coruña, Spain;Information and Communication Technologies Department, Faculty of Informatics, University of A Coruña, Spain;Information and Communication Technologies Department, Faculty of Informatics, University of A Coruña, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

This work presents a tool which is an online implementation of the best machine learning-based model obtained after an exhaustive computational study. Twelve techniques were applied to schizophrenia data to obtain the results of this study and, with these, Quantitative Genotype - Disease Relationships (QDGRs) for disease prediction. Thus, the tool offers the possibility to introduce SNP sequences (which contain the SNPs considered in the study) in order to classify a patient. In the future, QDGR models could be extended to other diseases. The model implemented online is a linear neural network.