Data mining for microrna gene prediction: On the impact of class imbalance and feature number for microrna gene prediction

2013 8th International Symposium on Health Informatics and Bioinformatics, HIBIT 2013

Volumn , Issue , 2013, Pages

  Saçar, Müşerref Duygu ^a   Allmer, Jens ^a  

^a IZMIR INSTITUTE OF TECHNOLOGY   (Turkey)

Author keywords

Class imbalance; Data mining; Feature selection; Machine learning; MicroRNA; MiRNA gene prediction

Indexed keywords

BIOINFORMATICS; DATA MINING; FEATURE EXTRACTION; FORECASTING; GENE EXPRESSION; LEARNING SYSTEMS; TOOLS;

CLASS IMBALANCE; EXPERIMENTAL METHODS; GENE PREDICTION; MICRORNAS; NON-CODING RNAS; POSITIVE DATA; POST-TRANSCRIPTIONAL; PRECISION AND RECALL;

RNA;

EID: 84892650223     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HIBIT.2013.6661685     Document Type: Conference Paper

References (21)

1. R. C. Lee, R. L. Feinbaum, and V. Ambros, "The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.," Cell, vol. 75, no. 5, pp. 843-54, Dec. 1993.
2. A. Rodriguez, S. Griffiths-Jones, J. L. Ashurst, and A. Bradley, "Identification of mammalian microRNA host genes and transcription units," Genome Research, vol. 14, no. 10A, pp. 1902-1910, Oct. 2004.
3. S. Pfeffer, M. Zavolan, F. A. Grässer, M. Chien, J. J. Russo, J. Ju, B. John, A. J. Enright, D. Marks, C. Sander, and T. Tuschl, "Identification of virus-encoded microRNAs," Science, vol. 304, no. 5671, pp. 734-6, Apr. 2004.
4. A. Aravin and T. Tuschl, "Identification and characterization of small RNAs involved in RNA silencing.," FEBS Letters, vol. 579, no. 26, pp. 5830-40, Oct. 2005.
5. K. L. S. Ng and S. K. Mishra, "De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures.," Bioinformatics, vol. 23, no. 11, pp. 1321-30, Jun. 2007.
6. J. Allmer and M. Yousef, "Computational methods for ab initio detection of microRNAs.," Frontiers in genetics, vol. 3, p. 209, Jan. 2012.
7. M. D. Saçar and J. Allmer, "Comparison of four Ab Initio MicroRNA Prediction Tools," in 4th International Conference on Bioinformatics Models, Methods and Algorithms, 2013.
8. J. Ding, S. Zhou, and J. Guan, "MiRenSVM: towards better prediction of microRNA precursors using an ensemble SVM classifier with multi-loop features.," BMC bioinformatics, vol. 11 Suppl 1, no. Suppl 11, p. S11, Jan. 2010.
9. W. Ritchie, D. Gao, and J. E. J. Rasko, "Defining and providing robust controls for microRNA prediction.," Bioinformatics (Oxford, England), vol. 28, no. 8, pp. 1058-61, Apr. 2012.
10. M. Yousef, S. Jung, L. C. Showe, and M. K. Showe, "Learning from positive examples when the negative class is undetermined-microRNA gene identification.," Algorithms for molecular biology, vol. 3, p. 2, Jan. 2008.
11. S. Griffiths-Jones, "miRBase: microRNA sequences and annotation.," Current protocols in bioinformatics/editoral board, Andreas D. Baxevanis ... [et al.], vol. Chapter 12, p. Unit 12.9.1-10, Mar. 2010.
12. S.-D. Hsu, F.-M. Lin, W.-Y. Wu, C. Liang, W.-C. Huang, W.-L. Chan, W.-T. Tsai, G.-Z. Chen, C.-J. Lee, C.-M. Chiu, C.-H. Chien, M.-C. Wu, C.-Y. Huang, A.-P. Tsou, and H.-D. Huang, "miRTarBase: a database curates experimentally validated microRNA-target interactions.," Nucleic acids research, vol. 39, no. Database issue, pp. D163-9, Jan. 2011.
13. M. D. Saçar, H. Hamzeiy, and J. Allmer, "Can MiRBase Provide Positive Data for Machine Learning for the Detection of MiRNA Hairpins?," Journal of integrative bioinformatics, vol. 10, no. 2, p. 215, Jan. 2013.
14. I. Bentwich, "Prediction and validation of microRNAs and their targets," FEBS Letters, vol. 579, no. 26, pp. 5904-5910, Oct. 2005.
15. A. Gudy, M. W. Szcze Niak, M. Sikora, and I. Makalowska, "HuntMi: an efficient and taxon-specific approach in pre-miRNA identification.," BMC bioinformatics, vol. 14, no. 1, p. 83, Mar. 2013.
16. P. Flicek, I. Ahmed, M. R. Amode, D. Barrell, K. Beal, S. Brent, et al., "Ensembl 2013.," Nucleic acids research, Nov. 2012.
17. P. Jiang, H. Wu, W. Wang, W. Ma, X. Sun, and Z. Lu, "MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features," Nucleic Acids Research, vol. 35, no. Web Server issue, pp. W339-344, Jul. 2007.
18. I. Bentwich, "Identifying human microRNAs.," Current Topics In Microbiology And Immunology, vol. 320, pp. 257-69, Jan. 2008.
19. T. Curk, J. Demsar, Q. Xu, G. Leban, U. Petrovic, I. Bratko, G. Shaulsky, and B. Zupan, "Microarray data mining with visual programming.," Bioinformatics, vol. 21, no. 3, pp. 396-8, 2005.
20. M. V. Cakir and J. Allmer, "Systematic computational analysis of potential RNAi regulation in Toxoplasma gondii," in Health Informatics and Bioinformatics (HIBIT), 2010 5th International Symposium on, 2010, pp. 31-38.
21. E. Amaldi and V. Kann, "On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems," Theoretical Computer Science, vol. 209, no. 1-2, pp. 237-260, 1998.