TY - JOUR
T1 - A Data Fusion Approach to Enhance Association Study in Epilepsy
AU - Marini, Simone
AU - Limongelli, Ivan
AU - Rizzo, Ettore
AU - Malovini, Alberto
AU - Errichiello, Edoardo
AU - Vetro, Annalisa
AU - Da, Tan
AU - Zuffardi, Orsetta
AU - Bellazzi, Riccardo
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Among the scientific challenges posed by complex diseases with a strong genetic component, two stand out. One is unveiling the role of rare and common genetic variants; the other is the design of classification models to improve clinical diagnosis and predictive models for prognosis and personalized therapies. In this paper, we present a data fusion framework merging gene, domain, pathway and protein-protein interaction data related to a next generation sequencing epilepsy gene panel. Our method allows integrating association information from multiple genomic sources and aims at highlighting the set of common and rare variants that are capable to trigger the occurrence of a complex disease. When compared to other approaches, our method shows better performances in classifying patients affected by epilepsy.
AB - Among the scientific challenges posed by complex diseases with a strong genetic component, two stand out. One is unveiling the role of rare and common genetic variants; the other is the design of classification models to improve clinical diagnosis and predictive models for prognosis and personalized therapies. In this paper, we present a data fusion framework merging gene, domain, pathway and protein-protein interaction data related to a next generation sequencing epilepsy gene panel. Our method allows integrating association information from multiple genomic sources and aims at highlighting the set of common and rare variants that are capable to trigger the occurrence of a complex disease. When compared to other approaches, our method shows better performances in classifying patients affected by epilepsy.
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U2 - 10.1371/journal.pone.0164940
DO - 10.1371/journal.pone.0164940
M3 - Article
AN - SCOPUS:85006833607
SN - 1932-6203
VL - 11
JO - PLoS One
JF - PLoS One
IS - 12
M1 - e0164940
ER -