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
miR164
cof-miR164f
Accession:
B21769071
Entry
Homologs
Rfam Alignments
Targets
Entry
ID:
cof-miR164f
Alias:
F42585.L000044.A25*
Sequence:
CAUGUGCCCCUCUUCCCCAUC
Description:
microRNA MIR164 predicted
Species:
山茱萸
  Species latin name:
Cornus officinalis
TCM Name:
Shanzhuyu(山茱萸)
TCM Resource (Sample number):
山茱萸(1)
Predicted by
Mirnovo
:
-
Evidence support:
Infernal
Experimental status:
Not yet
Homologs
miRBase Homologs
None
Bencao Homologs
cas-miR164
;
cof-miR164f
;
csp-miR164c
;
Rfam Alignments
>> MIR164  microRNA MIR164
 rank     E-value  score  bias mdl mdl from   mdl to       seq from      seq to       acc trunc   gc
 ----   --------- ------ ----- --- -------- --------    ----------- -----------      ---- ----- ----
  (1) !    0.0058   16.6   0.0  cm       81      101 ~~           1          21 + ~~ 1.00 5'&3' 0.62
                                                                    ?????????  ???????? ?      NC
                                                              ~~~~~~>>>>>>>>>-->>>>>>>>->~~~~~ CS
                                                   MIR164   1 <[80]*CAcGUGCcCuuCUUCuCCAuC*[8]> 109
                                                                    CA GUGCCC+UCUUC CCAUC
                                              csp-miR164c   1 <[ 0]*CAUGUGCCCCUCUUCCCCAUC*[0]> 21
                                                              ......*********************..... PP
Targets
Predicted by TargetFinder
NM_001083909
;  
NM_001104595
;  
NM_001109977
;  
NM_001143996
;  
NM_001143997
;  
NM_001161354
;  
NM_001166425
;  
NM_001282617
;  
NM_001282618
;  
NM_001282619
;  
NM_001282620
;  
NM_001291085
;  
NM_001347819
;  
NM_001347820
;  
NM_001347821
;  
NM_001347822
;  
NM_001347823
;  
NM_001347824
;  
NM_001347825
;  
NM_001347826
;  
NM_001348694
;  
NM_001349913
;  
NM_001349914
;  
NM_001349915
;  
NM_001349916
;  
NM_002070
;  
NM_006324
;  
NM_017911
;  
NM_018245
;  
NM_020904
;  
NR_144682
;  
NR_144683
;  
NR_144684
;  
NR_144685
;  
NR_144686
;  
NR_146323
;  
Predicted by TAPIR
NM_001008220
;  
NM_001083909
;  
NM_001104595
;  
NM_001143996
;  
NM_001143997
;  
NM_001166425
;  
NM_001282617
;  
NM_001282618
;  
NM_001282619
;  
NM_001282620
;  
NM_001291085
;  
NM_001347819
;  
NM_001347820
;  
NM_001347821
;  
NM_001347822
;  
NM_001347823
;  
NM_001347824
;  
NM_001347825
;  
NM_001347826
;  
NM_001349913
;  
NM_001349914
;  
NM_001349915
;  
NM_001349916
;  
NM_001364170
;  
NM_002070
;  
NM_006650
;  
NM_017911
;  
NM_018245
;  
NR_144682
;  
NR_144683
;  
NR_144684
;  
NR_144685
;  
NR_146323
;