Deep learning of cross-species single-cell landscapes identifies conserved regulatory programs underlying cell types.
Li J, Wang J, Zhang P, Wang R, Mei Y, Sun Z, Fei L, Jiang M, Ma L, E W, Chen H, Wang X, Fu Y, Wu H, Liu D, Wang X, Li J, Guo Q, Liao Y, Yu C, Jia D, Wu J, He S, Liu H, Ma J, Lei K, Chen J, Han X, Guo G.
Li J, et al. Among authors: e w.
Nat Genet. 2022 Nov;54(11):1711-1720. doi: 10.1038/s41588-022-01197-7. Epub 2022 Oct 13.
Nat Genet. 2022.
PMID: 36229673
Using these uniformly constructed cross-species landscapes, we developed a deep-learning-based strategy, Nvwa, to predict gene expression and identify regulatory sequences at the single-cell level. We systematically compared cell-type-specific transcription factors to reve …
Using these uniformly constructed cross-species landscapes, we developed a deep-learning-based strategy, Nvwa, to predict gene expression an …