Bridging the gap between AI and the life sciences: towards a standardized multi-omics data type

Omics data are key for the understanding of life and for improving human health but the contributions of AI in the field of multi-omics analysis are scarce when compared to single omics or medical imaging. We believe the major reason behind this fact is the lack of a standardized multi-omics data type. In this position paper, we introduce this problem, discuss some controversial aspects, and sketch a possible solution, as biomedical researchers clearly realized that there can be no real precision medicine without truly integrated multi-omics analysis and are desperately calling for collaboration. Our proposed multi-omics data type would provide a standardized way of storing raw and preprocessed multi-omics data together with preprocessing methods, therefore greatly simplifying data analysis and facilitating the participation of AI practitioners.