Intra- and inter-multi-omics interaction analysis using deep learning

Multi-omics interactions, including intra- and inter-omics interactions as well as socio-environmental influences, are key to uncovering molecular mechanisms that may be missed by individual omics analysis or conventional integration approaches. Deep learning offers a promising solution to overcome current limitations, including the complexity of modeling high-dimensional, nonlinear interactions, limited sample size and multiple testing burden.