If you entered more than one target, you must choose the
type of
intersection:
- All Associations - searching for associations that
correspond to either one of the targets.
The output will display
all miRNA - pharmacogenomic sets that include one of the search terms
you entered.
- Overlapping Associations - searching for associations that
correspond to all targets in the input list. The list must contain
targets from only 1 of 3 possible categories of targets.
The
output will display miRNA - pharmacogenomic sets that include units
which are shared by at least two of the search terms.
For more information see:
About Pharmaco-miR
Pharmaco-miR includes miRNA targeting data from several different
sources:
Please notice that when several databases are included in the search,
they are combined in an OR mode, therefore a miRNA target only has to
be identified in one of the databases to occur in the output.
For more information see:
About Pharmaco-miR
miRecords consists of experimentally verified miRNA targets
annotated from literature.
For more information see:
miRecords or
miRecords: an integrated resource for microRNA-target interactions;
Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T. Nucleic Acids Res. 2009
Jan;37(Database issue):D105-10
mirTarBase consists of experimentally verified miRNA targets
annotated from literature.
For more information see:
miRTarBase
or
miRTarBase: a database curates experimentally validated
microRNA-target interactions; Hsu SD, Lin FM, Wu WY, Liang C, Huang WC,
Chan WL, Tsai WT, Chen GZ, Lee CJ, Chiu CM, Chien CH, Wu MC, Huang CY,
Tsou AP, Huang HD. Nucleic acids research, 2011 Jan;39(Database
issue):D163-9
miRNA targeting data from
TargetScan can be filtered in two
different ways:
- The miRNA targets may be evolutionarily conserved or
non-conserved
- The miRNAs may be broadly conserved, conserved or poorly
conserved in evolution
Please notice that selecting a target site conservation level is
mandatory, for Pharmaco-miR to search the TargetScan entries.
For more information see:
TargetScan
FAQ or
Most Mammalian mRNAs Are Conserved Targets
of MicroRNAs; Robin C Friedman, Kyle Kai-How Farh, Christopher B Burge,
David P Bartel. Genome Research, 19:92-105 (2009)
miRanda predicted target sites are scored by a machine learning
algorithm named miRSVR.
- Targets are divided into high miRSVR score (28% of targets)
and low miRSVR score (the remaining 72% of targets)
- miRNAs are divided into evolutionarily conserved and
non-conserved miRNAs
For more information see:
miRanda
or
Comprehensive modeling of microRNA targets predicts
functional non-conserved and non-canonical sites; Betel D, Koppal A,
Agius P, Sander C, Leslie C., Genome Biology 2010 11:R90
PITA miRNA targets are generated by scoring a variety of
features, including spatial structure of the target region.
Targets are separated into ‘
top predictions’ (with strong seed
and high conservation) and ‘
all predictions’.
For more
information see:
PITA
or
The role of site accessibility in microRNA target
recognition; Michael Kertesz, Nicola Iovino, Ulrich Unnerstall, Ulrike
Gaul & Eran Segal. Nature Genetics 39, 1278 - 1284 (2007)
Pharmaco miR 