MiSTAR: MiRNA target prediction through modeling quantitative and qualitative miRNA binding site information in a stacked model structure

Nucleic Acids Research

Volumn 45, Issue 7, 2017, Pages

  Van Peer, Gert ^a   De Paepe, Ayla ^b   Stock, Michiel ^b   Anckaert, Jasper ^a,b   Volders, Pieter Jan ^a,b   Vandesompele, Jo ^a,b   De Baets, Bernard ^b   Waegeman, Willem ^b  

^a GHENT UNIVERSITY HOSPITAL   (Belgium)

^b GHENT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

MESSENGER RNA; MICRORNA; 3' UNTRANSLATED REGION;

3' UNTRANSLATED REGION; ALGORITHM; ARTICLE; BINDING SITE; CONTROLLED STUDY; HUMAN; INTERACTIONS WITH RNA; LOGISTIC REGRESSION ANALYSIS; MIRNA STACKED MODEL TARGET; PREDICTION; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; QUANTITATIVE ANALYSIS; RANDOM FOREST; BIOLOGICAL MODEL; EVALUATION STUDY; MACHINE LEARNING; METABOLISM; SOFTWARE;

3' UNTRANSLATED REGIONS; ALGORITHMS; BINDING SITES; HUMANS; MACHINE LEARNING; MICRORNAS; MODELS, GENETIC; RNA, MESSENGER; SOFTWARE;

EID: 85019065208     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkw1260     Document Type: Article

References (26)

1. Esteller, M. (2011) Non-coding RNAs in human disease. Nat. Rev. Genet., 12, 861-874.
2. Huntzinger, E. and Izaurralde, E. (2011) Gene silencing by microRNAs: contributions of translational repression and mRNA decay. Nat. Rev. Genet., 12, 99-110.
3. Hausser, J. and Zavolan, M. (2014) Identifcation and consequences of miRNA-target interactions-beyond repression of gene expression. Nat. Rev. Genet., 15, 599-612.
4. Thomson, D.W., Bracken, C.P. and Goodall, G.J. (2011) Experimental strategies for microRNA target identifcation. Nucleic Acids Res, 39, 6845-6853.
5. Reyes Herrera, P.H. and Ficarra, E. (2012) One decade of development and evolution of microRNA target prediction algorithms. Genomics Proteomics Bioinformatics, 10, 254-263.
6. Peterson, S.M., Thompson, J.A., Ufkin, M.L., Sathyanarayana, P., Liaw, L. and Congdon, C.B. (2014) Common features of microRNA target prediction tools. Front. Genet., 5, 23.
7. Bewick, V., Cheek, L. and Ball, J. (2005) Statistics review 14: logistic regression. Crit. Care, 9, 112-118.
8. Breiman, L. (2001) Random forests. Mach. Learn., 45, 5-32.
9. Betel, D., Koppal, A., Agius, P., Sander, C. and Leslie, C. (2010) Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol., 11, R90.
10. Reczko, M., Maragkakis, M., Alexiou, P., Grosse, I. and Hatzigeorgiou, A.G. (2012) Functional microRNA targets in protein coding sequences. Bioinformatics, 28, 771-776.
11. Wang, X. and El Naqa, I.M. (2008) Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics, 24, 325-332.
12. Bandyopadhyay, S. and Mitra, R. (2009) TargetMiner: microRNA target prediction with systematic identifcation of tissue-specifc negative examples. Bioinformatics, 25, 2625-2631.
13. Grimson, A., Farh, K.K.-H., Johnston, W.K., Garrett-Engele, P., Lim, L.P. and Bartel, D.P. (2007) MicroRNA targeting specifcity in mammals: determinants beyond seed pairing. Mol. Cell, 27, 91-105.
14. Friedman, J., Hastie, T. and Tibshirani, R. (2010) Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw., 33, 1-22.
15. Liaw, A. and Wiener, M. (2002) Classifcation and regression by randomForest. R News, 2, 18-22.
16. Fawcett, T. (2004) ROC graphs: notes and practical considerations for researchers. Mach. Learn., 31, 1-38.
17. Davis, J. and Goadrich, M. (2006) The relationship between precision-recall and ROC curves. Proc. 23rd Int. Conf. Mach. Learn., 233-240.
18. John, B., Enright, A.J., Aravin, A., Tuschl, T., Sander, C. and Marks, D.S. (2004) Human microRNA targets. Plos Biol., 2, e363.
19. Garcia, D.M., Baek, D., Shin, C., Bell, G.W., Grimson, A. and Bartel, D.P. (2011) Weak seed-pairing stability and high target-site abundance decrease the profciency of lsy-6 and other microRNAs. Nat. Struct. Mol. Biol., 18, 1139-1146.
20. Kertesz, M., Iovino, N., Unnerstall, U., Gaul, U. and Segal, E. (2007) The role of site accessibility in microRNA target recognition. Nat. Genet., 39, 1278-1284.
21. Sing, T., Sander, O., Beerenwinkel, N. and Lengauer, T. (2005) ROCR: visualizing classifer performance in R. Bioinformatics, 21, 3940-3941.
22. Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J.-C. and Müller, M. (2011) pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics, 12, 77.
23. DeLong, E.R., DeLong, D.M. and Clarke-Pearson, D.L. (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics, 44, 837-845.
24. Hollander, M., Wolfe, D.A. and Chicken, E. (2013) In: Nonparametric statistical methods. 3rd edn. John Wiley & Sons, pp. 316-321.
25. Zeileis, A., Wiel, M.A., Hornik, K. and Hothorn, T. (2008) Implementing a class of permutation tests: the coin package. J. Stat. Softw., 28, 1-23.
26. Park, Y. and Marcotte, E.M. (2012) Flaws in evaluation schemes for pair-input computational predictions. Nat. Methods, 9, 1134-1136.