Table 1.

List of software, websites, and references to methods for sequence-based miR target prediction and method for inferring miR–target relationships using paired expression profiles of miRs and genes in single-cancer datasets.

SEQUENCE BASED METHODS FOR miR TARGET PREDICTION (PREDICTING WHETHER A GIVEN mRNA IS TARGETED BY A miR)
METHOD/REFERENCE/SOFTWARE	DATA TYPES	COMMENTS
TargetRank Nielsen et al.62 http://hollywood.mit.edu/targetrank/	*mRNA sequence	*scoring system based on sequence complementarity and conservation
miRanda Enright et al.114	*mRNA sequence	*sequence complementarity and estimated minimum free energy *source code in C freely available
TargetScan (Version 7) Agarwal et al.69 http://www.targetscan.org/vert_71/	*mRNA sequence	*scoring system based on 14 features found to be informative of binding efficacy using a regression model
STarMir Rennie et al.70 http://sfold.wadsworth.org/cgi-bin/starmir.pl	*mRNA sequence	*model for binding site predictions trained on miR binding sites from CLIP data
miRanda-miRSVR Betel et al.64 http://www.microrna.org/microrna/home.do	*mRNA sequence	*regression model trained on miRanda predicted target site features and miR transfection data to predict target site binding efficacy

METHODS FOR INFERRING miR–TARGET RELATIONSHIPS USING PAIRED MIR AND GENE EXPRESSION PROFILES IN SINGLE-CANCER DATASETS
METHOD	DATA TYPES	COMMENTS
Correlation coefficient based methods Peng et al.47	*miR & gene expression *sequence predicted targets	*Proposed permutation based method to estimate FDR of MTIs
MLR Yang et al.17	*miR & gene expression *sequence predicted targets *CNA *PM	*models gene expression by a linear combination of all miR expression profiles (adjusting for epigenetic and genomic effects)
LASSO Lu et al.52	*miR & gene expression	*models gene expression given multiple potentially competing miRs
Elastic net regression Sass et al.82	*miR & gene expression	*found superior performance for identification of experimentally validated MTIs versus LASSO and PCC
Causal inference (IDA) Le et al.88	*miR & gene expression	*ensemble of LASSO, PCC, and IDA detected more MTIs than any single method
Maximal information content (MIC) Le et al.88	*miR & gene expression	*mutual information based method to detect linear and non-linear associations between two variables
GenmiR++ Huang et al.51	*miR & gene expression *sequence predicted targets	*Bayesian inference method for MTI prediction

Abbreviations: FDR, false discovery rate; MTI, miR–target interactions; UTR, untranslated region; LASSO, least absolute shrinkage and selection operator; PM, DNa promoter methylation; CNA, copy number abnormalities; PCC, Pearson’s correlation coefficient; IDA, interventional calculus when the directed acyclic graph is absent; CLIP, crosslinking and immunoprecipitation.