Detailed information of deep learning profile BP001379.1

This page shows detailed deep learning-derived predictions and motifs for CREB3 in K562 using a single trained BPNet model.

Model details

Name: CREB3
Model ID: BP001379.1
Cell line/tissue: K562
Class: Basic leucine zipper factors (bZIP)
Family: CREB-related factors
JASPAR ID: MA0638.2
Taxon: Vertebrates
Species: Homo sapiens
Data Type: ChIP-seq
Uniprot ID: O43889  
Source: ENCSR093FKD
Model: BPNet
Download trained model
Download TF-MoDISco Report

Contribution weight matrix (CWM)

A [ 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 -0.00 0.00 0.00 0.00 0.00 0.00 0.00 ]
C [ 0.00 0.00 0.00 0.00 -0.00 0.00 0.00 -0.00 0.01 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 ]
G [ 0.00 0.00 -0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 -0.00 0.00 ]
T [ 0.00 -0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.01 0.00 -0.00 0.00 0.00 0.00 0.00 0.00 ]

Frequency matrix

A [ 9 12 12 8 14 9 13 20 18 11 9 10 13 13 8 12 6 13 9 12 8 6 0 1 46 0 0 0 1 34 0 10 22 8 13 10 9 7 4 8 5 9 8 9 4 8 8 9 13 14 ]
C [ 14 7 14 21 12 12 17 12 13 11 8 17 18 15 17 17 22 3 11 18 14 1 5 7 2 48 0 0 27 0 42 29 5 15 13 16 9 11 14 9 25 19 9 16 19 17 13 19 15 20 ]
G [ 19 24 9 13 13 19 8 15 13 23 26 20 16 13 17 11 12 14 20 1 24 43 0 42 2 0 51 0 22 15 1 9 12 19 15 13 18 22 20 23 12 9 13 20 12 13 17 14 15 8 ]
T [ 9 8 16 9 12 11 13 4 7 6 8 4 4 10 9 11 11 21 11 20 5 1 46 1 1 3 0 51 1 2 8 3 12 9 10 12 15 11 13 11 9 14 21 6 16 13 13 9 8 9 ]

Hypothetical CWM

A [ 0.00 0.00 0.00 -0.00 0.00 -0.00 -0.00 0.01 -0.00 0.00 -0.00 -0.00 0.01 -0.00 0.00 0.00 0.00 0.00 0.00 ]
C [ -0.00 -0.00 0.00 0.00 -0.00 0.00 0.00 -0.01 0.01 -0.01 0.00 0.00 -0.01 0.01 0.00 -0.00 0.00 0.00 0.00 ]
G [ -0.00 0.00 -0.00 0.00 0.00 -0.01 0.00 -0.00 -0.01 0.01 -0.01 0.00 0.00 -0.00 -0.00 -0.00 -0.00 -0.00 -0.00 ]
T [ 0.00 -0.00 0.00 0.00 -0.00 0.01 -0.00 -0.00 -0.00 -0.00 0.01 -0.00 -0.00 0.00 -0.00 0.00 0.00 -0.00 0.00 ]

Other motifs identified by TF-MoDISco

Motif name: counts.pos_patterns.pattern_0

Num. of seqlets: 3032

Motif name: counts.pos_patterns.pattern_1

Num. of seqlets: 772

Motif name: counts.pos_patterns.pattern_2

Num. of seqlets: 470

Motif name: counts.pos_patterns.pattern_3

Num. of seqlets: 147