Cross-modal predictive modeling of multi-omic data in 3D airway organ tissue equivalents during viral infection.
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| Title: | Cross-modal predictive modeling of multi-omic data in 3D airway organ tissue equivalents during viral infection. |
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| Authors: | Rezapour M; Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC, United States., McNutt PM; Wake Forest Institute for Regenerative Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, United States., Ornelles DA; Microbiology Immunology, Wake Forest University School of Medicine, Winston-Salem, NC, United States., Walker SJ; Wake Forest Institute for Regenerative Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, United States., Murphy SV; Wake Forest Institute for Regenerative Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, United States., Atala A; Wake Forest Institute for Regenerative Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, United States., Gurcan MN; Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC, United States. |
| Source: | Frontiers in genetics [Front Genet] 2025 Sep 25; Vol. 16, pp. 1658577. Date of Electronic Publication: 2025 Sep 25 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101560621 Publication Model: eCollection Cited Medium: Print ISSN: 1664-8021 (Print) Linking ISSN: 16648021 NLM ISO Abbreviation: Front Genet Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1664-8021 |
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| DOI: | 10.3389/fgene.2025.1658577 |
