The Bencao (Herbal) Database（本草数据库）

  1. OmicsAtlas
  2. TranscriptomeAtlas
  3. miRNA Atlas
  4. miR164
  5. cas-miR164

Accession: B13271468

Entry

ID: cas-miR164
Alias: F42585.L000044.A25*
Sequence: CAUGUGCCCCUCUUCCCCAUC
Description: microRNA MIR164 predicted
Species: 积雪草  Species latin name: Centella asiatica
TCM Name: Jixuecao(积雪草)  
TCM Resource (Sample number): 积雪草(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 ;