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 0.01 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 0.00 0.00 -0.00 0.00 0.00 ]
G [ 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 ]
T [ 0.00 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 ]

Frequency matrix

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

Hypothetical CWM

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