SNP-schizo: A web tool for schizophrenia SNP sequence classification

Vanessa Aguiar-Pulido, José A. Seoane, Cristian R. Munteanu, Alejandro Pazos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationAdvances in Computational Intelligence - 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Proceedings
Number of pages8
EditionPART 2
StatePublished - 2011
Externally publishedYes
Event11th International Work-Conference on on Artificial Neural Networks, IWANN 2011 - Torremolinos-Malaga, Spain
Duration: Jun 8 2011Jun 10 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6692 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Work-Conference on on Artificial Neural Networks, IWANN 2011


  • bioinformatics
  • data mining
  • machine learning
  • neural networks
  • schizophrenia
  • SNP

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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