1. OmicsAtlas
  2. TranscriptomeAtlas
  3. miRNA Atlas
  4. miR167
  5. apl-miR167h

Accession: B07610436

Entry

ID: apl-miR167h
Alias: F123.K001796.A11
Sequence: UGAAGCUGCCAGCAUGAUCC
Description: microRNA MIR167_1 predicted
Species: 龙牙草  Species latin name: Agrimonia pilosa
TCM Name: Xianhecao(仙鹤草)  
TCM Resource (Sample number): 仙鹤草(1)
Predicted by Mirnovo: -
Evidence support: Infernal
Experimental status: Not yet


Rfam Alignments

>> MIR167_1  microRNA MIR167_1
 rank     E-value  score  bias mdl mdl from   mdl to       seq from      seq to       acc trunc   gc
 ----   --------- ------ ----- --- -------- --------    ----------- -----------      ---- ----- ----
  (1) !     0.003   19.1   0.0  cm       14       33 ~~           1          20 + ~~ 1.00 5'&3' 0.55
                               ??? ?????  ?????????       NC
                         ~~~~~~<<<-<<<<<--<<<<<<<<<~~~~~~ CS
             MIR167_1  1 <[13]*UGAAGCUGCCAGCAUGAuCU*[97]> 130
                               UGAAGCUGCCAGCAUGAUC
          vum-miR167h  1 <[ 0]*UGAAGCUGCCAGCAUGAUCC*[ 0]> 20
                         ......********************...... PP

Targets

Predicted by TargetFinder

NM_000071 ;   NM_001005176 ;   NM_001005751 ;   NM_001018057 ;   NM_001024843 ;   NM_001080509 ;   NM_001159770 ;   NM_001162501 ;   NM_001178005 ;   NM_001178008 ;   NM_001178009 ;   NM_001197244 ;   NM_001198773 ;   NM_001198774 ;   NM_001198775 ;   NM_001278451 ;   NM_001278452 ;   NM_001278453 ;   NM_001282356 ;   NM_001282357 ;   NM_001291398 ;   NM_001301061 ;   NM_001307960 ;   NM_001308026 ;   NM_001308319 ;   NM_001320298 ;   NM_001321072 ;   NM_001321073 ;   NM_001321981 ;   NM_001330102 ;   NM_001330220 ;   NM_001330504 ;   NM_001330721 ;   NM_001346743 ;   NM_001346744 ;   NM_001352127 ;   NM_001352156 ;   NM_001352157 ;   NM_001352158 ;   NM_001352691 ;   NM_001352692 ;   NM_001352693 ;   NM_001354006 ;   NM_001354007 ;   NM_001354008 ;   NM_001354009 ;   NM_001354010 ;   NM_001354012 ;   NM_001354014 ;   NM_001354015 ;   NM_001369623 ;   NM_001369624 ;   NM_001369625 ;   NM_001369626 ;   NM_001369628 ;   NM_001369629 ;   NM_001370301 ;   NM_001370302 ;   NM_001370528 ;   NM_001707 ;   NM_002651 ;   NM_005632 ;   NM_006576 ;   NM_007237 ;   NM_012293 ;   NM_013253 ;   NM_014801 ;   NM_015088 ;   NM_015881 ;   NM_017614 ;   NM_019109 ;   NM_020880 ;   NM_025134 ;   NM_025141 ;   NM_031961 ;   NM_031963 ;   NM_052832 ;   NM_078474 ;   NM_133640 ;   NM_134266 ;   NM_139177 ;   NM_153000 ;   NM_172364 ;   NM_175709 ;   NM_198859 ;   NR_024248 ;   NR_036682 ;   NR_120673 ;   NR_121624 ;   NR_135280 ;   NR_148682 ;  

Predicted by TAPIR

NM_000783 ;   NM_001005176 ;   NM_001005751 ;   NM_001024843 ;   NM_001080837 ;   NM_001159397 ;   NM_001159398 ;   NM_001159770 ;   NM_001162501 ;   NM_001165412 ;   NM_001178008 ;   NM_001178009 ;   NM_001197244 ;   NM_001242412 ;   NM_001247996 ;   NM_001278451 ;   NM_001278452 ;   NM_001278453 ;   NM_001291398 ;   NM_001301061 ;   NM_001307960 ;   NM_001308026 ;   NM_001308319 ;   NM_001311160 ;   NM_001311162 ;   NM_001318392 ;   NM_001319226 ;   NM_001321072 ;   NM_001321073 ;   NM_001330102 ;   NM_001330332 ;   NM_001330504 ;   NM_001346743 ;   NM_001346744 ;   NM_001352127 ;   NM_001352156 ;   NM_001352157 ;   NM_001352158 ;   NM_001352691 ;   NM_001352692 ;   NM_001352693 ;   NM_001354006 ;   NM_001354007 ;   NM_001354008 ;   NM_001354009 ;   NM_001354010 ;   NM_001354012 ;   NM_001354014 ;   NM_001354015 ;   NM_001362924 ;   NM_001362925 ;   NM_001362926 ;   NM_001364170 ;   NM_001370528 ;   NM_001372050 ;   NM_001707 ;   NM_003998 ;   NM_005632 ;   NM_006288 ;   NM_006576 ;   NM_007079 ;   NM_007237 ;   NM_012293 ;   NM_015088 ;   NM_018482 ;   NM_019109 ;   NM_020700 ;   NM_020731 ;   NM_025134 ;   NM_025141 ;   NM_032329 ;   NM_032611 ;   NM_052938 ;   NM_057157 ;   NM_078474 ;   NM_133640 ;   NM_139177 ;   NM_153000 ;   NM_153833 ;   NM_172364 ;   NM_175709 ;   NM_198859 ;   NR_024248 ;   NR_036682 ;   NR_120673 ;   NR_121624 ;   NR_131236 ;   NR_135280 ;   NR_148682 ;   NR_164077 ;