Big data integration to understand complex disease

The rapid generation of -omic data sets has been on the incline for several years, representing massive investments by NIH. These data include but are not limited to transcriptomics, epigenomics, protein structuralomics, genomics, microbiomics, metabolomics, and high- throughput phenotyping. Yet the synergy of these datasets has lagged, particularly when it comes to understanding why at a physiological-organism level certain genes correlate with very detailed phenotypes, driving specific genotype-to-phenotype events. In this call, we solicit papers that find novel ways of integrating datasets or applying datasets to explain details and mechanisms of disease genotype-to-phenotype correlations at an organism level. The deadline for this new call is 12.31.2019. For further pre-submission enquiries, please contact Dr. Leah Solberg Woods (