BoNB 1.2 – Biomarker Selection and Classification from Genome-wide SNP data

BoNB 1.2

:: DESCRIPTION

BoNB (Bag of Naïve Bayes), an algorithm for genetic biomarker selection and subjects classification from the simultaneous analysis of genome-wide SNP data. BoNB is based on the Naïve Bayes classification framework, enriched by three main features: bootstrap aggregating of an ensemble of Naïve Bayes classifiers, a novel strategy for ranking and selecting the attributes used by each classifier in the ensemble and a permutation-based procedure for selecting significant biomarkers, based on their marginal utility in the classification process. BoNB is tested on the Wellcome Trust Case-Control study on Type 1 Diabetes and its performance is compared with the ones of both a standard Naïve Bayes algorithm and HyperLASSO, a penalized logistic regression algorithm from the state-of-the-art in simultaneous genome-wide data analysis.

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::DEVELOPER

SYSTEMS BIOLOGY AND BIOINFORMATICS GROUP

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler

:: DOWNLOAD

 BoNB

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2012;13 Suppl 14:S2. doi: 10.1186/1471-2105-13-S14-S2. Epub 2012 Sep 7.
Bag of Naïve Bayes: biomarker selection and classification from genome-wide SNP data.
Sambo F, Trifoglio E, Di Camillo B, Toffolo GM, Cobelli C.

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