Comparison of four Ab initio MicroRNA prediction tools

BIOINFORMATICS 2013 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms

Volumn , Issue , 2013, Pages 190-195

  Saçar, Müserref Duygu ^a   Allmer, Jens ^a  

^a IZMIR INSTITUTE OF TECHNOLOGY   (Turkey)

Author keywords

Ab initio; Comparison; MiRNA; MiRNA prediction

Indexed keywords

AB INITIO; COMPARISON; COMPUTATIONAL TOOLS; EXPERIMENTAL VALIDATIONS; MIRNA; POST-TRANSCRIPTIONAL GENE SILENCING; RELATIVE PERFORMANCE; RNA-INDUCED SILENCING COMPLEXES;

ALGORITHMS; BIOINFORMATICS; FORECASTING; GENES; MATHEMATICAL MODELS;

RNA;

EID: 84877947791     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (37)

1. Altuvia, Y., Landgraf, P., Lithwick, G., Elefant, N., Pfeffer, S., Aravin, A., Brownstein, M. J., Tuschl, T., and Margalit, H., 2005. Clustering and conservation patterns of human microRNAs. Nucleic acids research 33, 2697-706.
2. Bentwich, I., 2008. Identifying human microRNAs. RNA interference 320, 257-269.
3. Bentwich, I., Avniel, A., Karov, Y., Aharonov, R., Gilad, S., Barad, O., Barzilai, A., Einat, P., Einav, U., Meiri, E., et al., 2005. Identification of hundreds of conserved and nonconserved human microRNAs. Nature genetics 37, 766-70.
4. Berezikov, E., Guryev, V., van de Belt, J., Wienholds, E., Plasterk, R. H. A., and Cuppen, E., 2005. Phylogenetic shadowing and computational identification of human microRNA genes. Cell 120, 21-4.
5. Borchert, G. M., Lanier, W., and Davidson, B. L., 2006. RNA polymerase III transcribes human microRNAs. Nature Structural & Molecular Biology 13, 1097- 1101.
6. Burgt, A. V. D., Fiers, M. W. J. E., Nap, J., and Van, R. C. H. J., 2012. In silico miRNA prediction in metazoan genomes : balancing between sensitivity and specificity. BMC Genomics 24, 1-24.
7. Cakir, M. V., and Allmer, J., 2010. Systematic computational analysis of potential RNAi regulation in Toxoplasma gondii. in Health Informatics and Bioinformatics, HIBIT), 2010 5th International Symposium on, Ankara, Turkey: IEEE), 31-38.
8. Cifuentes, D., Xue, H., Taylor, D. W., Patnode, H., Mishima, Y., Cheloufi, S., Ma, E., Mane, S., Hannon, G. J., Lawson, N. D., et al., 2010. A novel miRNA processing pathway independent of Dicer requires Argonaute2 catalytic activity. Science 328, 1694- 1698.
9. Ding, J., Zhou, S., and Guan, J., 2010. MiRenSVM: towards better prediction of microRNA precursors using an ensemble SVM classifier with multi-loop features. BMC Bioinformatics 11 Suppl 1, S11.
10. Elton, T. S., Martin, M. M., Sansom, S. E., Belevych, A. E., Györke, S., and Terentyev, D., 2011. miRNAs got rhythm. Life Sciences 88, 373-383.
11. Enright, A. J., John, B., Gaul, U., Tuschl, T., Sander, C., and Marks, D. S., 2003. MicroRNA targets in Drosophila. Genome Biology 5, R1.
12. Friedman, R. C., Farh, K. K.-H., Burge, C. B., and Bartel, D. P., 2009. Most mammalian mRNAs are conserved targets of microRNAs. Genome Research 19, 92-105.
13. Griffiths-Jones, S., Saini, H. K., van Dongen, S., and Enright, A. J., 2008. miRBase: tools for microRNA genomics. Nucleic acids research 36, D154-8.
14. Grundhoff, A., 2011. Computational prediction of viral miRNAs. Methods in Molecular Biology, Clifton, N.J. 721, 143-152.
15. Han, J., Lee, Y., Yeom, K.-H., Nam, J.-W., Heo, I., Rhee, J.-K., Sohn, S. Y., Cho, Y., Zhang, B.-T., and Kim, V. N., 2006. Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell 125, 887-901.
16. Hofacker, I. L., 2003. Vienna RNA secondary structure server. Nucleic Acids Research 31, 3429-3431.
17. Jiang, P., Wu, H., Wang, W., Ma, W., Sun, X., and Lu, Z., 2007. MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids Research 35, W339-344.
18. Lai, E. C., Tomancak, P., Williams, R. W., and Rubin, G. M., 2003. Computational identification of Drosophila microRNA genes. Genome Biol 4, R42.
19. Lee, R. C., Feinbaum, R. L., and Ambrost, V., 1993. The C . elegans Heterochronic Gene lin-4 Encodes Small RNAs with Antisense Complementarity to & II-14. Cell 75, 843-854.
20. Lee, Y., Kim, M., Han, J., Yeom, K.-H., Lee, S., Baek, S. H., and Kim, V. N., 2004. MicroRNA genes are transcribed by RNA polymerase II. The EMBO Journal 23, 4051-4060.
21. Liang, H., and Li, W.-H., 2009. Lowly expressed human microRNA genes evolve rapidly. Molecular biology and evolution 26, 1195-8.
22. Lu, J., Shen, Y., Wu, Q., Kumar, S., He, B., Shi, S., Carthew, R. W., Wang, S. M., and Wu, C.-I., 2008. The birth and death of microRNA genes in Drosophila. Nature genetics 40, 351-5.
23. Lund, E., Güttinger, S., Calado, A., Dahlberg, J. E., and Kutay, U., 2004. Nuclear export of microRNA precursors. Science 303, 95-8.
24. Morlando, M., Ballarino, M., Gromak, N., Pagano, F., Bozzoni, I., and Proudfoot, N. J., 2008. Primary microRNA transcripts are processed cotranscriptionally. Nature Structural & Molecular Biology 15.
25. Ng, K. L. S., and Mishra, S. K., 2007. De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures. Bioinformatics 23, 1321-30.
26. Okada, C., Yamashita, E., Lee, S. J., Shibata, S., Katahira, J., Nakagawa, A., Yoneda, Y., and Tsukihara, T., 2009. A high-resolution structure of the premicroRNA nuclear export machinery. Science 326, 1275-1279.
27. Pfeffer, S., Sewer, A., Lagos-Quintana, M., Sheridan, R., Sander, C., Grässer, F. A., van Dyk, L. F., Ho, C. K., Shuman, S., Chien, M., et al., 2005. Identification of microRNAs of the herpesvirus family. Nature Methods 2, 269-276.
28. Ritchie, W., Gao, D., and Rasko, J. E. J., 2012. Defining and providing robust controls for microRNA prediction. Bioinformatics, Oxford, England 28, 1058-61.
29. Rodriguez, A., Griffiths-Jones, S., Ashurst, J. L., and Bradley, A., 2004. Identification of mammalian microRNA host genes and transcription units. Genome Research 14, 1902-1910.
30. Steffen, P., Voss, B., Rehmsmeier, M., Reeder, J., and Giegerich, R., 2006. RNAshapes: an integrated RNA analysis package based on abstract shapes. Bioinformatics, Oxford, England 22, 500-3.
31. Suzuki, H. I., and Miyazono, K., 2011. Emerging complexity of microRNA generation cascades. Journal of biochemistry 149, 15-25.
32. Wu, Y., Wei, B., Liu, H., Li, T., and Rayner, S., 2011. MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences. BMC Bioinformatics 12, 107.
33. Xue, C., Li, F., He, T., Liu, G.-P., Li, Y., and Zhang, X., 2005. Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics 6, 310.
34. Yousef, M., Jung, S., Showe, L. C., and Showe, M. K., 2008. Learning from positive examples when the negative class is undetermined-microRNA gene identification. Algorithms for molecular biology : AMB 3, 2.
35. Yousef, M., Nebozhyn, M., Shatkay, H., Kanterakis, S., Showe, L. C., and Showe, M. K., 2006. Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier. Bioinformatics, Oxford, England 22, 1325-34.
36. Zeng, Y., and Cullen, B. R., 2004. Structural requirements for pre-microRNA binding and nuclear export by Exportin 5. Nucleic acids research 32, 4776-85.
37. Ørom, U. A., Nielsen, F. C., and Lund, A. H., 2008. MicroRNA-10a binds the 5'UTR of ribosomal protein mRNAs and enhances their translation. Molecular cell 30, 460-71.