Open access
Sep 2026
DeepSCENIC: transfer learning from sequence-to-function models enables causal gene regulatory network inference
Sequence-to-function (S2F) deep learning models have become an important aid to decipher the genomic cis-regulatory code. However, current S2F models do not take the cellular trans-environment of transcription factors (TF) into account. Conversely, methods for gene regulatory network (GRN) inference often rely on heuri...
Gabriele Partel, Seppe De Winter, Vasilis Konstantakos et al.
· bioRxiv · 0 citations