0000000000109821
AUTHOR
E. Ruggiero
Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural ne…
Searches for lepton number violation and resonances in K± → πμμ decays
The NA48/2 experiment at CERN collected a large sample of charged kaon decays to final states with multiple charged particles in 2003–2004. A new upper limit on the rate of the lepton number violating decay K±→π∓μ±μ± is reported: B(K±→π∓μ±μ±)<8.6×10−11 at 90% CL. Searches for two-body resonances X in K±→πμμ decays (such as heavy neutral leptons N4 and inflatons χ ) are also presented. In the absence of signals, upper limits are set on the products of branching fractions B(K±→μ±N4)B(N4→πμ) and B(K±→π±X)B(X→μ+μ−) for ranges of assumed resonance masses and lifetimes. The limits are in the (10−11,10−9) range for resonance lifetimes below 100 ps.