Detailed information of deep learning profile BP001293.1

  1. Home
  2. Deep Learning Profile > BP001293.1
This page shows detailed deep learning-derived predictions and motifs for NFIA in HepG2 using a single trained BPNet model.

Model details

Name: NFIA
Model ID: BP001293.1
Cell line/tissue: HepG2
Class: SMAD/NF-1 DNA-binding domain factors
Family: Nuclear factor 1
JASPAR ID: MA0670.2
Taxon: Vertebrates
Species: Homo sapiens
Data Type: ChIP-seq
Uniprot ID: Q12857  
Source: ENCSR226QQM
Model: BPNet
Download trained model
Download TF-MoDISco Report

Sequence logo

 

Contribution weight matrix (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 -0.00 -0.00 0.00 0.04 0.02 0.00 0.00 0.00 ]
C [ 0.00 0.00 0.00 0.01 -0.00 0.00 0.00 0.07 0.00 0.00 0.00 0.00 -0.00 -0.00 0.09 0.12 0.00 -0.00 0.00 -0.00 0.00 ]
G [ 0.00 -0.00 0.00 -0.00 0.00 0.12 0.10 -0.00 -0.00 0.00 0.00 0.01 0.00 0.03 0.00 -0.00 -0.00 0.01 0.00 0.00 0.00 ]
T [ 0.00 0.00 0.00 0.02 0.06 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 [ 2930 3001 2977 3017 2893 2781 2685 3022 3204 3019 2934 2927 2891 2859 3037 3117 3049 3280 1339 482 99 0 36 714 5796 2263 3269 2973 3155 391 157 3 9116 5507 2941 3255 2971 2566 3017 2822 2730 2876 2847 3202 2925 2913 2981 2964 3014 2932 ]
C [ 3096 3065 3094 3114 3098 3121 3221 3148 2861 2965 3190 3121 3343 3129 2997 2695 3030 2802 5289 5074 18 0 0 11422 1984 3855 2848 2550 1309 891 11513 12182 2215 779 2666 2878 3251 3529 3037 3215 3209 2986 3151 3060 3255 3034 3028 3263 3245 3099 ]
G [ 3180 3140 3078 3003 3098 3299 3113 3139 3174 3222 3209 3115 3116 3169 3192 3660 3160 2544 2648 297 584 12192 12149 34 675 3716 3224 4297 3598 6003 9 4 185 5002 5008 2982 2964 2768 3167 3219 3254 3182 3182 2967 2959 3050 3224 3123 2989 3058 ]
T [ 2989 2989 3046 3061 3106 2994 3176 2886 2956 2989 2862 3032 2845 3038 2969 2723 2956 3569 2919 6342 11494 3 10 25 3740 2361 2854 2375 4133 4910 516 6 679 907 1580 3080 3009 3332 2974 2939 3002 3151 3015 2966 3056 3198 2962 2845 2947 3106 ]

Hypothetical CWM

   
A [ -0.00 -0.00 0.00 -0.01 -0.03 -0.04 -0.05 -0.02 0.02 0.02 0.01 0.01 0.00 0.01 -0.03 -0.02 -0.05 0.06 0.04 0.01 0.00 0.00 0.00 ]
C [ 0.00 0.01 0.01 0.01 0.02 -0.02 -0.03 -0.06 0.07 0.02 0.02 0.02 0.01 -0.00 -0.02 0.09 0.12 0.01 -0.02 0.01 0.00 0.00 0.00 ]
G [ 0.01 0.01 -0.00 0.01 -0.03 0.01 0.12 0.10 -0.03 0.00 0.01 0.02 0.02 0.02 0.06 -0.06 -0.03 -0.02 0.02 0.01 0.01 0.01 0.01 ]
T [ 0.00 0.00 0.01 0.01 0.04 0.06 -0.05 -0.02 -0.04 0.01 0.00 0.00 0.00 0.01 0.02 -0.01 -0.04 -0.04 -0.02 -0.01 0.00 -0.00 -0.00 ]

Other motifs identified by TF-MoDISco

 

Motif name: counts.pos_patterns.pattern_1

Num. of seqlets: 4953

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_2

Num. of seqlets: 2829

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_3

Num. of seqlets: 2107

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_4

Num. of seqlets: 1821

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_5

Num. of seqlets: 764

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_6

Num. of seqlets: 704

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_7

Num. of seqlets: 691

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_8

Num. of seqlets: 183

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_9

Num. of seqlets: 107

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_13

Num. of seqlets: 31

CWM

PFM

     

HCWM