Mingon Kang and Eunyoung Jang (both Computer Science) published a perspective article entitled, "Intra- and inter-multi-omics interaction analysis using deep learning" in Bioinformatics Advances. This article provides insight of multi-omics interactions and how deep learning deals with. This article is written by the collaborator, Tesfaye Mersha from Indiana University, School of Medicine. 

The abstract is: 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.