Cross-modal predictive modeling of multi-omic data in 3D airway organ tissue equivalents during viral infection
These results provide insights into the host's molecular response to viral infections and highlight MASIT as a robust tool for analyzing high-dimensional, small-sample multi-omics datasets.
Authors
- Patrick McNutt (ORCID: https://orcid.org/0000-0002-5703-4565)
- Stephen J. Walker (ORCID: https://orcid.org/0000-0002-0732-2366)
- Mostafa Rezapour (ORCID: https://orcid.org/0000-0001-9569-118X)
- David A. Ornelles (ORCID: https://orcid.org/0000-0002-5151-8382)
- Anthony Atala (ORCID: https://orcid.org/0000-0001-8186-2160)
- Sean V. Murphy (ORCID: https://orcid.org/0000-0002-2820-2451)
- Metin N. Gürcan (ORCID: https://orcid.org/0000-0002-2421-8229)
Institutions
- Forest Institute (US)
- Wake Forest University (US)
Publication Details
- Journal
- Frontiers in Genetics
- Published
- 2025-09-24
- DOI
- https://doi.org/10.3389/fgene.2025.1658577
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00