Machine learning to probe transcription factor combinatorics
Transcription factors (TFs) act in a combinatorial manner competing and collaborating to regulate their target genes. Several questions remain regarding the conservation of these combinations among different gene classes, regulatory regions and cell types. Here we propose a new machine learning approach able to infer these combinations of TFs. This approach demonstrates that TF combinatorics are conserved for different gene … Continue reading Machine learning to probe transcription factor combinatorics