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The analysis of gene networks and signalling pathways plays a key role in understanding gene functions, i.e., their effects on the development of a particular disease. Yet, for many heterogeneous diseases, the number of known disease-associated genes is limited. Identifying disease-associated genes is still an open challenge. To understand the functions of genes associated with a disease, we develop a Metropolis-Hastings sampling based SIGnificant NETwork (MSIGNET) identification approach.doi:10.21926/obm.genet.2002107 fatcat:247isvcgk5cjpp3swm4pdoqjmi