| No. |
Tool |
Species |
Method in brief |
Availability |
| 1 |
MiRanda
Enright et al.
, John et
al. [68,75,76] |
Drosophila,
Vertebrates |
Evolutionary conservation, binding energy, weighted score using base pairs, gap penalties |
http://www.microrna.org/microrna/getDownloads.do
(Stand-alone application) |
| 2 |
TargetScan
Lewis et al. [74] |
Vertebrates |
Seed match, Match outside seed region, Conservation of seed region |
http://genes.mit.edu/tscan/targetscanS.html (Web application) |
| 3 |
RNAhybrid
Rehmsmeier [18] |
Drosophila |
Negative normalized minimum free energy values based on length of target sequence and length of mi-
croRNA, shows statistical significance of predicted targets |
http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/dl_pre-page.html (Stand-alone application) |
| 4 |
DIANA-microT
Kirikidou et al. [77] |
Human, Mouse |
Search restricted 3' UTR of mRNAs, Minimum energy of potential sequence (38 nt) in comparison with 100 complementary sequence, filtering based on microRNA associated proteins |
http://diana.cslab.ece.ntua.gr/microT/(Web application, can
download the software on request) |
| 5 |
TargetScanS
Lewis et al. [17] |
Vertebrates |
Simple version of TargetScan, perfect seed match, scoring based on dynamic programming |
http://genes.mit.edu/tscan/targetscanS2005.html
(Web application) |
| 6 |
PicTar Kerk et al. [70,73] |
Drosophila,
Vertebrates |
Search limited to conservative 3' UTR regions, scoring by HMM and multiple sequence alignment with eight vertebrate species |
http://pictar.mdc-berlin.de/
(Web application) |
| 7 |
RNA22
Huynh et al. [78],
Phillipe L et al. [79] |
C.elegans,
Human,
Drosophila,
Mouse |
Initial identi_cation of putative sites by pattern match (with-out knowing targeting microRNAs), then associate microRNA with target(user defined parameters- minimum number of base pairs, maximum number of unpaired bases, maximum allowed free energy) |
http://cbcsrv.watson.ibm.com/rna22.html
(Web application) |
| 8 |
MicroTar
Rahul and Mortti [80] |
C.elegans,
Drosophila,
mouse |
No evolutionary conservation constraint, seed match and free energy(RNAlib) are deciding parameters |
http://tiger.dbs.nus.edu.sg/microtar/
(Stand-alone application) |
| 9 |
NBmiRTar
Yousef et al. [81]
|
human, mouse,
y, worm, ze-
bra_sh |
Do not require sequence conservation, based on seed match and outside features of microRNA:mRNA
duplex, and Naive Bayes classifier |
http://wotan.wistar.upenn.edu/NBmiRTar/
(Web application) |
| 10 |
PiTA Kertesz et
al. [82] |
Human,Mouse,y
C.elegans, |
Secondary structure, Seed region with single mismatch or G:U wobble, Free energy of miRNA:mRNA structure |
http://genie.weizmann.ac.il/pubs/mir07/mir07_data.html
(Stand-alone application) |
| 11 |
targetRank
Cydney et al. [83] |
Human, mouse |
Conservation, Sequence alignment with 16 vertebrate genome, Seed match |
http://genes.mit.edu/targetrank/
(Web application) |
| 12 |
miRDB Xiaowei [84,85] |
Human,
mouse, rat,
dog, chicken |
Target prediction by the tool MirTarget2 |
http://mirdb.org/miRDB/index.html
(Web application) |
| 13 |
MiRtif
Yuchen et al. [86]
|
Worm, Mouse,
Human, Fly |
Support vector machine microRNA:mRNA interaction filter. predicted microRNA interactions
from miRanda, PicTar, and TargetScanS are further filtered using SVM |
http://bsal.ym.edu.tw/mirtif
(Web application) |
| 14 |
MTar
Chandra et al. [71]
|
Human |
Structural, positional, thermodynamic properties and machine learning with ANN |
http://www.mca.cet.ac.in/research.htm
(Stand-alone application) |
| 15 |
targetSpy
Martin et al. [87]
|
Human,mouse,
rat, chicken,y |
Evolutionary conservation and perfect seed match are not a criteria, based on ranked structural, base
pairing properties (45 parameters) with machine learning |
http://www.targetspy.org/ (Web application) |
| 16 |
psRNATarget
Xinbin Dai et
al. [88] |
Plant |
Reverse complementary matching score between microRNA and mRNA, unpaired energy required
to open secondary structure of mRNA |
http://plantgrn.noble.org/psRNATarget
(Web application) |
| 17 |
MiRTar Hsu et al. [89] |
Human |
microRNA target are determined using TargetScan, miRanda, PITA, and RNAHybrid. Also find extend of biological function of microRNA by estimating over
expression in KEGG pathways |
http://mirtar.mbc.nctu.edu.tw/human/
(Web application) |
| 18 |
comiR Claudia
Coronnello et al. [90] |
Human |
Single probabilistic score calculated from microRNA target score from four popular target finding tools,PITA, miRanda, TargetScan and mirSVR |
http://www.benoslab.pitt.edu/comir/index2.php (Web
application) |
| 19 |
HomoTarget
Hamed Ahmadi et al. [88] |
Human |
Pattern recognition neural network (PRNN) based classifier. Initial sequence alignment, then seed match
based filtering, followed by PRNN |
http://lbb.ut.ac.ir/Download/LBBsoft/homoTarget/ (Stand-
alone application) |
| 20 |
starBase
V2.0 Jun-
Hao Li et al. [91] |
Human |
microRNA targets are identified using prediction overlap from five tools, TargetScan, miRanda,
Pictar2, PITA and RNA22, while finding ceRNA interactions |
http://starbase.sysu.edu.cn/targetSite.php
(Web application) |
