Funnily enough, I had to do something similar recently. After a good amount of backgrond research, it turns out that this is the best/well-cited resource for this.

Let me know what you think!

AnimalTFDB 4.0

You can use an R package called dorothea to access gene regulatory transcription factors. It contains a comprehensive resources of curated collection of TFs and their target genes.

library(dorothea)
library(OmnipathR)
library(decoupleR)

#it is available for only human and mouse
net <- decoupleR::get_dorothea(levels = c('A', 'B', 'C', 'D'), organism = "human")
[2023-08-29 09:44:20] [SUCCESS] [OmnipathR] Loaded 278830 interactions from cache.
head(net)
# A tibble: 6 × 4
  source confidence target   mor
  <chr>  <chr>      <chr>  <dbl>
1 MYC    A          TERT    1   
2 JUN    D          SMAD3   0.25
3 SMAD3  A          JUN     1   
4 JUN    D          SMAD4   0.25
5 SMAD4  A          JUN     1   
6 RELA   D          FAS     0.25
#confidence level go from A to D, A bing the most confident and D being the less
#mor:mode of regulation (-1 or 1), one for each confidence level. Bigger values will generate weights close to zero

#subsetting table for MYC gene (a TF)
myc <- net[net$source %in% c("MYC"),]
head(myc)
# A tibble: 6 × 4
  source confidence target   mor
  <chr>  <chr>      <chr>  <dbl>
1 MYC    A          TERT       1
2 MYC    A          ENO1       1
3 MYC    A          CDC25A     1
4 MYC    A          CXCR4      1
5 MYC    A          CDKN1A    -1
6 MYC    A          TP53       1