CrossAttOmics: multiomics data integration with cross-attention.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Advances in high throughput technologies enabled large access to various types of omics. Each omics provides a partial view of the underlying biological process. Integrating multiple omics layers would help have a more accurate diagnosis. However, the complexity of omics data requires approaches that can capture complex relationships. One way to accomplish this is by exploiting the known regulatory links between the different omics, which could help in constructing a better multimodal representation.

Authors

  • Aurélien Beaude
    IBISC, Université Paris-Saclay, Univ Evry, 23 Boulevard de France, Evry-Courcouronnes 91020, France.
  • Franck Augé
    Artificial Intelligence & Deep Analytics, Omics Data Science, Sanofi R&D Data and Data Science, 1 Av. Pierre Brossolette, Chilly-Mazarin 91385, France.
  • Farida Zehraoui
    IBISC - IBGBI, University of Evry, 91037 Evry CEDEX, France.
  • Blaise Hanczar
    IBISC, Univ Evry, Université Paris-Saclay, 23 boulevard de France, 91034, Evry, France. blaise.hanczar@ibisc.univ-evry.fr.