SPECTRA: predicting cellular perturbation responses with Graph Learning over Gene Regulatory Networks
The results show that graph-based signal propagation is a biologically grounded alternative to latent-shift perturbation modeling and can improve the recovery of sparse perturbation-induced transcriptional effects.
Michele Calabrò, Patrick Sheehan, F. Cambuli et al.
· bioRxiv · 0 citations