This page shows detailed deep learning-derived predictions and motifs for E4F1 in K562 using a single trained BPNet model. Please scroll down the page to browse other models for this transcription factor.
Model details
| Name: | E4F1 |
| Model ID: | BP001176.1 |
| Cell line: | K562 |
| Class: | C2H2 zinc finger factors |
| Family: | Factors with multiple dispersed zinc fingers |
| JASPAR ID: | UN0801.1 |
| Taxon: | Vertebrates |
| Species: | Homo sapiens |
| Data Type: | ChIP-seq |
| Uniprot ID: | Q66K89 |
| Source: | ENCODE |
| Model: | BPNet |
| Download trained model | |
| Download TF-MoDISco Report |
Other motifs identified by TF-MoDISco
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Number of seqlets:
Unique motifs
This is a placeholder for the motifs that are found to be specific to this particular model, i.e., not found in other models trained for E4F1.