Performance and evaluation of microRNA gene identification tools

Journal of Proteomics and Bioinformatics

Volumn 2, Issue 8, 2009, Pages 336-343

  Sinha, Swati ^a   Vasulu, T S ^a   de Rajat, K ^a  

^a INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

Accuracy; BayesMiRNAfind; BayesSVMmiRNAfind; Mathew's correlation coefficient; MiPred; OneClassmiRNAfind; Positive predictive value; Sensitivity; Specificity; Triplet SVM

Indexed keywords

ANIMALIA;

EID: 75649152856     PISSN: None     EISSN: 0974276X     Source Type: Journal    
DOI: 10.4172/jpb.1000093     Document Type: Article

References (39)

1. Adai A, Johnson C, Mlotshwa S, Evans SA, Manocha V, et al. (2005) Computational prediction of miRNAs in Arabidopsis thaliana. Genome Research, 15: 78-91.
2. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116: 281-297.
3. Bentwich I (2005) Prediction and validation of microRNAs and their targets. FEBS Lett 579: 5904-5910.
4. Berezikov E, Guryev V, Belt JV, Weinholds E, Plasterk RHA, et al. (2005) Phylogenetic Shadowing and Computational Identification Of Human microRNA genes. Cell 120: 21-24.
5. Bonnet E, Wuyts J, Rouze P, Peer YV (2004) Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativa identify important target genes. PNAS 101: 11511-11516.
6. Brameier M, Wiuf C. (2007) Ab initio identification of human microRNAs based on structure motifs. BMC Bioinformatics 8: 478.
7. Clop A, Marcq F, Takeda H, Pirottin D, Tordoir X (2006) A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep. Nature Genetics 38: 813-818.
8. Dezulian T, Remmert M, Palatnik JF, Weigel D, Huson DH (2006) Identification of plant microRNA homologs. Bioinformatics 22: 359-360.
9. Dror G, Sorek R, Shamir R (2005) Accurate identification of alternatively spliced exons using support vector machine. Bioinformatics 21: 897-901.
10. Feng J, Sun G, Yan J, Noltner K, Li W, et al. (2009) Evidence for X-chromosomal schizophrenia assoaciated with miRNA alterations. PLoS ONE 4: e6121.
11. Frank E, Hall M, Trigg L, Holmes G, Witten I (2004) Data mining in bioinformatics using Weka. Bioinformatics 2 479-2481.
12. Gard OS, Thomassen, Rosok O, Rognes T (2006) Computational Prediction of MicroRNAs Encoded in Viral and Other Genomes. Journal of Biomedicine and Biotechnology Article ID 95270: 1-10.
13. Griffiths-Jones S, Saini HK, Van DS, Enright AJ (2008) miRBase: tools for microRNA genomics. Nucleic Acid Research 36: D154-D158.
14. Griffiths-Jones S, Grocock RJ, Van DS, Bateman A, Enright AJ (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acid Research 34: D140-D144.
15. Griffiths-Jones S (2004) The microRNA Registry. Nucleic Acid Research 32: D109-D111.
16. Gruber AR, Neubock R, Hofacker IL, Washietl S. (2007) The RNAz web server: prediction of thermodynamically stable and evolutionarily conserved RNA structures. Nucleic Acids Research 35: W335-W338.
17. Helvik SA, Snove O, Saetrom P (2007) Reliable prediction of Drosha processing sites improves microRNA gene prediction. Bioinformatics Genome Analysis 23: 142-149.
18. Hertel JA, Stadler PF (2006) Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data. Bioinformatics 22: e197-e202.
19. Hofacker IL (2003) Vienna RNA secondary structure server. Nucleic Acids Research 31: 3429-3431.
20. Jiang P, Wu H, Wang W, Wa M, Sun X, et al. (2007) MiPred: classification of real and pseudo microRNA precursor using random forest prediction model with combined features. Nucleic acid research, 35: W339-W344.
21. Jones SG (2004) The microRNA Registry. Nucleic Acids Research 32: D109-D111.
22. Lai EC, Tomancak P, Williams RW, Rubin GM (2003) Computational identification of Drosophila microRNA genes. Genome Biology 4: R42.
23. Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75: 843-854.
24. Lim LP, Lau NC, Weinstein EG, Abdelhakim A, Yekta S, et al. (2003) The microRNAs of Caenorhabditis elegans. Genes & Development 17: 991-1008.
25. Lindow M, Gorodkin J (2007a) Principles and Limitations Computational MicroRNA Gene and Target Finding. Dna and Cell Biology 26: 339-351.
26. Lindow M, Krogh A (2005) Computational evidence for hundreds of non-conserved plant microRNAs. BMC Genomics 6: 119.
27. Lindow M, Jacobsen A, Nygaard S, Mang Y, Krogh A (2007) Intragenomic Matching Reveals a Huge Potential for miRNA-MediatedRegulation in Plants. PLoS Comput Biol 3: 2379-2390.
28. Nam JW, Shin KR, Han J, Lee Y, Kim VN, et al. (2005) Human microRNA prediction through probabilistic colearning of sequence and structure. Nucleic Acids Research 33: 3570-3581.
29. Paul SA, Landgraf P, Aravin A, Pfeffer S, Brownstein MJ, et al. (2005) Identification of clustered microRNAs using an ab initio prediction Method. BMC Bioinformatics 6: 267.
30. Sethupathy P, Megraw M, Hatzigeorgiou AG (2006) A guide through present computational approaches for the identification of mammalian microRNA targets. Nature Methods 3: 881-886.
31. Sheng Y, Engstrom PG, Lenhard B (2007) Mammalian MicroRNA Prediction through a Support VectorMachine Model of Sequence and Structure. PloS ONE 9: e946.
32. Szafranski K, Megraw M, Reczko M, Hatzigeorgiou AG Support Vector Machines for predicting microRNA Hairpins.
33. Wang X, Zhang J, Li F, Gu J, He T, et al. (2005) MicroRNA identification based on sequence and structure alignment. Bioinformatics 21: 3610-3614.
34. Wightman B, Ha I, Ruvkun G (1993) Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell 75: 855-862.
35. Xue C, Li F, He T, Liu GP, Li Y, et al. (2005) Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics 6: 310.
36. Yoon S, Micheli GD (2006) Computational Identification of MicroRNAs and Their Targets. Birth Defects Research 78: 118-128.
37. Yousef M, Jung S, Showe LC, Showe MK (2008) Learning from positive examples when the negative class is undetermined-microRNA gene identification. Algorithms for Molecular Biology 3: 2.
38. Yousef M, Nebozhyn M, Shatkay H, Kanterakis S, Showe LC, et al. (2006) Combining multi-species genomic data for microRNA identification using a naive Bayes classifier. Bioinformatics 22: 1325-1334.
39. Zheng Y, Hsu W, Lee ML, Wong LS Exploring Essential Attributes For Detecting MicroRNA Precursors From Background Sequences.