The Bencao (Herbal) Database(本草数据库)
miRNA_Atlas(miRNA地图)
sRNA_Atlas(sRNA地图)
miRNA_Target(miRNA靶基因)
sRNA_Target(sRNA靶基因)
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About(关于)
OmicsAtlas
TranscriptomeAtlas
miRNA Atlas
miR159
gma-miR159aq
Accession:
B34156841
Entry
Homologs
Rfam Alignments
Targets
Entry
ID:
gma-miR159aq
Alias:
F1317.J000013.A11
Sequence:
UUGGAUUGAAGGGAGCUCG
Description:
microRNA MIR159 predicted
Species:
大豆
  Species latin name:
Glycine max
TCM Name:
Dadouhuangjuan(大豆黄卷)
Dandouchi(淡豆豉)
Heidou(黑豆)
TCM Resource (Sample number):
大豆黄卷(1)
黑豆(1)
Predicted by
Mirnovo
:
-
Evidence support:
Infernal
Experimental status:
Not yet
Homologs
miRBase Homologs
None
Bencao Homologs
apl-miR159ax
;
ave-miR159k
;
gma-miR159aq
;
llc-miR159i
;
lpu-miR159bd
;
mca-miR159ap
;
pav-miR159ar
;
pfr-miR159l
;
por-miR159av
;
rja-miR159au
;
Rfam Alignments
>> MIR159  microRNA MIR159
 rank     E-value  score  bias mdl mdl from   mdl to       seq from      seq to       acc trunc   gc
 ----   --------- ------ ----- --- -------- --------    ----------- -----------      ---- ----- ----
  (1) !    0.0033   17.9   0.0  cm      165      182 ~.           1          18 + ~. 1.00    5' 0.50
                                  ???????  ???????? NC
                          ~~~~~~~->>>>>>>-->>>>>>>> CS
               MIR159  13 <[152]*UUGGAcuGAAGGGAGCUC 182
                                 UUGGA UGAAGGGAGCUC
         rja-miR159au   1 <[  0]*UUGGAUUGAAGGGAGCUC 18
                          .......****************** PP
Targets
Predicted by TargetFinder
NM_000476
;  
NM_001024455
;  
NM_001031684
;  
NM_001047160
;  
NM_001134774
;  
NM_001134775
;  
NM_001134776
;  
NM_001167671
;  
NM_001167672
;  
NM_001184773
;  
NM_001184774
;  
NM_001184775
;  
NM_001184776
;  
NM_001184777
;  
NM_001195272
;  
NM_001195446
;  
NM_001242412
;  
NM_001256850
;  
NM_001267550
;  
NM_001267556
;  
NM_001267558
;  
NM_001267559
;  
NM_001271634
;  
NM_001288824
;  
NM_001288825
;  
NM_001288826
;  
NM_001288827
;  
NM_001288828
;  
NM_001318121
;  
NM_001318122
;  
NM_001318734
;  
NM_001321265
;  
NM_001321266
;  
NM_001321267
;  
NM_001363802
;  
NM_001368133
;  
NM_003319
;  
NM_005260
;  
NM_005288
;  
NM_005444
;  
NM_005578
;  
NM_005863
;  
NM_013232
;  
NM_018383
;  
NM_020731
;  
NM_021115
;  
NM_022822
;  
NM_031889
;  
NM_033400
;  
NM_133378
;  
NM_133432
;  
NM_133437
;  
NM_138694
;  
NM_138799
;  
NM_170724
;  
NR_003713
;  
NR_024872
;  
NR_024873
;  
NR_073040
;  
NR_073390
;  
NR_109833
;  
NR_135598
;  
NR_135599
;  
NR_135600
;  
NR_135603
;  
NR_135604
;  
NR_135605
;  
Predicted by TAPIR
NM_000476
;  
NM_001004434
;  
NM_001024455
;  
NM_001025356
;  
NM_001031684
;  
NM_001047160
;  
NM_001134774
;  
NM_001134775
;  
NM_001134776
;  
NM_001142678
;  
NM_001142679
;  
NM_001184773
;  
NM_001184774
;  
NM_001184775
;  
NM_001184776
;  
NM_001184777
;  
NM_001195272
;  
NM_001195446
;  
NM_001204803
;  
NM_001218
;  
NM_001242412
;  
NM_001256850
;  
NM_001267550
;  
NM_001267556
;  
NM_001267558
;  
NM_001267559
;  
NM_001271634
;  
NM_001293642
;  
NM_001300860
;  
NM_001318121
;  
NM_001318122
;  
NM_001318734
;  
NM_001363802
;  
NM_001370182
;  
NM_001370183
;  
NM_001370184
;  
NM_001370185
;  
NM_001370186
;  
NM_003319
;  
NM_004686
;  
NM_005444
;  
NM_005863
;  
NM_013232
;  
NM_014829
;  
NM_018383
;  
NM_020731
;  
NM_021115
;  
NM_022822
;  
NM_031912
;  
NM_032513
;  
NM_133378
;  
NM_133432
;  
NM_133437
;  
NM_138694
;  
NM_170724
;  
NM_181519
;  
NM_206925
;  
NR_003713
;  
NR_073040
;  
NR_073390
;  
NR_109833
;  
NR_125341
;  
NR_135511
;  
NR_146089
;