Computational approaches in detecting non- coding RNA

Current Genomics

Volumn 14, Issue 6, 2013, Pages 371-377

  Wang, Chunyu ^a   Wei, Leyi ^b   Guo, Maozu ^a   Zou, Quan ^b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b XIAMEN UNIVERSITY   (China)

Author keywords

Bioinformatics; Deep sequencing; LncRNA; Machine learning; microRNA; Non coding RNA

Indexed keywords

MICRORNA; UNTRANSLATED RNA;

GENE EXPRESSION; HIDDEN MARKOV MODEL; HUMAN; MACHINE LEARNING; NORTHERN BLOTTING; PROTEIN FOLDING; PROTEIN STRUCTURE; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; REVIEW; SENSITIVITY AND SPECIFICITY; SEQUENCE HOMOLOGY;

EID: 84888104685     PISSN: 13892029     EISSN: 18755488     Source Type: Journal    
DOI: 10.2174/13892029113149990005     Document Type: Review

References (61)

1. Mattick JS, Makunin IV(2006) Non-coding RNA. Hum Mol Genet, 15(Spec No. 1): R17-R29.
2. Lingling Hu, Yong Huang, Qicong Wang, Quan Zou, Yi Jiang. (2012) A benmark comparison of ab initio microRNA identification methods and software. Genetics and Molecular Research. 11(4): 4525-4538.
3. Leyi Wei, Yong Huang, Yanyun Qu, Yi Jiang, Quan Zou. (2012) Computational analysis of miRNA target identification. Current Bioinformatics, 7(4): 512-525.
4. Kapranov, P., Willingham, A. T. and Gingeras, T. R(2007). Genome-wide transcription and the implications for genomic organization. Nat. Rev. Genet, 8: 413-423.
5. Eddy SR(2007). Non-coding RNA genes and the modern RNA world. Nat Rev Genet, 2: 919-929.
6. Yong Huang, Quan Zou, Shun Ming Tang, Li Gang Wang, Xing Jia Shen(2010). Computational identification and characteristics of novel microRNAs from the silkworm (Bombyx mori L.). Molecular Biology Reports, 37: 3171-3176.
7. Wang Xiu-Jie, J. L. R., Nam-Hai Chua, Terry Gaasterland (2004) Prediction and identification of Arabidopsis thaliana microRNA genes and their mRNA targets. Genome Biology, 5: R65.
8. Eugenia Wang. (2009) MicroRNA Regulation and its Biological Significance in Personalized Medicine and Aging. Current Genomics, 10(3): 143.
9. Livny J, Waldor MK(2007). Identification of small RNAs in diverse bacterial species. Curr-opin Microbiol 10(2): 96-1001.
10. Klein, R. J, Ziva Misulovin, Sean R. Eddy(2002). Noncoding RNA genes identified in AT-rich hyperthermophiles. PNAS. 99: 7542-7547.
11. Chenghai Xue, Fei Li, Tao He, Guoping Liu, Yanda Li, Xuegong Zhang (2005). Classification of Real and Pseudo MicroRNA Precursors Using Local Structure-Sequence Features And Support Vector Machine. BMC Bioinformatics, 6: 310.
12. Jana Hertel, Danielle de Jong, Manja Marz, Dominic Rose, Hakim Tafer, Andrea Tanzer, Bernd Schierwater, Peter F. Stadler (2009). Non-coding RNA annotation of the genome of Trichoplax adhaerens. Nucleic Acids Research, 37: 1602-1615.
13. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ(1990). Basic local alignment search tool. J Mol Biol, 215: 403-10.
14. Pearson WR(2000). Flexible sequence similarity searching with the FASTA3 program package. Method Mol Biol, 132: 185-219.
15. Pearson W(1991). Searching protein sequence libraries: comparison of the sensitivity and selectivity of the Smith-Waterman and FASTA algorithms. Genomic, 11: 635-650.
16. Kent WJ (2002). Blat: the BLAST-like aligment tool. Genome Res, 12: 656-664.
17. Xue Q. D. Wang, Jennifer L Crutchley, Josee Dostie. (2011) Shaping the Genome with Non-Coding RNAs. Current Genomics, 12(5): 307-321.
18. Eddy SR(2002). A memory efficient dynamic programming algorithm for optimal structural alignment of a sequence to an RNA secondary structure. BMC Bionformatic, 3, 18.
19. Klein, R. J. and Eddy, S. R(2003). RSEARCH: finding homologs of single structured RNA sequences. BMC Bioinformatics, 4, 44.
20. Zhang S, Haas B, Eskin E, Bafna V(2005). Searching Genomes for Noncoding RNA Using FastR. IEEE/ACM Trans Comput Biol Bioinform. 2(4): 366-379.
21. Gautheret, D. and Lambert, A(2001). Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles. J. Mol. Biol, 313, 1003-1011.
22. Xiaowo Wang, Jing Zhang, Fei Li, Jin Gu, Tao He, Xuegong Zhang, Yanda Li (2005). Sequence analysis: MicroRNA identification based on sequence and structure alignment. Bioinformatics, 21: 3610-3614.
23. Sumeet Agarwal, Candida Vaz, Alok Bhattacharya, Ashwin Srinivasan. (2010) Prediction of novel precursor miRNAs using a context-sensitive hidden Markov model (CSHMM). BMC Bioinformatics, 11: S29.
24. Hao-Yue Fu, Ding-Yu Xue, Xiang-de Zhang, Pei-Ying Yang. (2009) Assessing potential miRNA targets based on a Markov model. Genet. Mol. Res. 8: 848-860.
25. S. R. Eddy. (2002) Computational genomics of noncoding RNA genes, Cell, 109: 137-140.
26. Sam. Griffiths-Jones, Alex. Bateman, Mhairi. Marshall, Ajay Khanna, Sean R. Eddy. (2003) Rfam: an RNA family database, Nucleic Acids Res, 31: 439-441.
27. Badger jH, Olsen Gj(1999). CRITICA: Coding region identification tool invoking comparative analysis. Mol. Bio. Evol, 16: 512-524.
28. Tiziana Castrignano, Alessandro Canali, Giorgio Grillo, Sabino Liuni, Flavio Mignone, Graziano Pesole (2004). CSTminer: a web tool for the identification of coding and noncoding conserved sequence tags through cross-species genome comparison. Nucleic Acids Res, 32: 624-627.
29. Lotta C, Iseli C, Jongeneel C V, Bucher P. (2003). Modeling sequencing errors by combining Hidden Markov models. Bioinformatics, 19: 103-112.
30. Quan Zou, Chen Lin, Xiaoyan Liu, Yingpeng Han, Wenbin Li, Maozu Guo. (2011) Novel representation of RNA secondary structure used to improve prediction algorithms. Genetics and Molecular Research, 10 (3): 1986-1998.
31. Liu J, Gough J, Rost B(2006). Distinguishing protein-coding from non-coding RNAs through support vector machines. PLoS Genet, 2: 29.
32. Lei Kong, Yong Zhang, Zhi-Qiang Ye, Xiao-Qiao Liu, Shu-Qi Zhao, Liping Wei and Ge Gao. (2007) CPC: assess the proteincoding potential of the transcripts using sequence features and support vector machine. Nucleic Acids Res, 35: 345-349.
33. Mathews DH, Turner DH(2006) prediction of RNA secondary structure by free energy minimization. Curr Opin Struct Biol, 16(3): 270-278.
34. Hofacker IL(2003). Vienna RNA secondary structure server. Nucleic Acids Res, 31(13): 3429-3431.
35. Zuker M, Stiegler P(1981). Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res 9(1): 133-148.
36. Ogurtsov AY, Shabalina SA, Kondrashov AS, Roytberg MA(2006). Analysis of internal loops within the RNA secondary structure in almost quadratic time. Bioinformatics, 22(11): 1317-1324.
37. Chan C Y, Lawrence C E, Ding Y(2005). Structure clustering features on the Sfold Web server. Bioinformatics, 21: 3926-3928.
38. Sverker Edvardsson, Paul P. Gardner, Anthony M. Poole, Nichael D, Hendy, Dacid Penny, Vincent Moulton (2003). A search for H/ACA snoRNAs in yeast using MFE secondary structure prediction. Bioinformatics, 19: 865-873.
39. Rivas E, Eddy R(2000). Secondary structure alone is generally not statistically significant for the detection of noncoding RNAs. Bioinformatics, 16: 583-605.
40. Tran TT, Zhou F, Marshburn S, Stead M, Kushner SR, Xu Y(2009). De Novo computational prediction of non-coding RNA genes in prokaryotic genomes. Bioinformatics, 25: 2897-2905.
41. Peng Jiang, Haonan Wu, Wenkai Wang, Wei Ma, Xiao Sun, Zuhong Lu (2007). MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids Res, 35: W339-344.
42. Ping Xuan, Maozu Guo, Xiaoyan Liu, Yangchao Huang, Wenbin Li, Yufei Huang(2011). PlantMiRNAPred: efficient classification of real and pseudo plant pre-miRNAs. Bioinformatics, 27: 1368-1376.
43. Marc R Friedlander, Wei Chen, Catherine Adamidi, Jonas Maaskola, Ralf Einspanier, Signe Knespel, Nikolaus Rajewsky. (2008). Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol, 26: 407-15.
44. Sonika Tyagia, Candida Vaza, Vipin Guptab, Rohit Bhatiab, Sachin Maheshwaric, Ashwin Srinivasand, Alok Bhattacharya (2008). CID-miRNA: a web server for prediction of novel miRNA precursors in human genome. Biochem Biophys Res Commun. 372: 831-834.
45. Xu Y, Zhou X, Zhang W(2008). MicroRNA prediction with a novel ranking algorithm based on random walks. Bioinformatics, 24: i50-i58.
46. Simon Moxon, Frank Schwach, Tamas Dalmay, Dan MacLean, David J. Studholme, Vincent Moulton (2008). A toolkit for analyzing large-scale plant small RNA datasets. Bioinformatics, 24: 2252-2253.
47. Erle Zhu, Fangqing Zhao, Gang Xu, Huabin Hou, LingLin Zhou, Xiaokun Li, Zhongsheng Sun and Jinyu Wu (2010). mirTools: microRNA profiling and discovery based on high-throughput sequencing. Nucleic Acids Res, 38: W392-W397.
48. Michael Hackenberg, Martin Sturm, David Langenberger, Juan Manuel Falcon-Perez and Ana M. Aransay (2009). miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res, 37: 68-76.
49. Chad J. Creighton, Jeffrey G. Reid, Preethi H(2009). Gunaratne. Expression profliling of microRNAs by deep sequencing. Briefings in Bioinformatics, 10: 490-497.
50. Victor Ambros, Bonnie Bartel, David P. Bartel, Christopher B. Burge, James C. Carrington, Xuemei Chen, Gideon Dreyfuss, Sean R Eddy, Sam Griffiths-Jones, Mhairi Marshall, Marjori Matzke, Gary Ruvkun, And Thomas Tusch (2003). A uniform system for microRNA annotation. RNA, 9: 277-279.
51. Jian-Hua Yang, Xiao-Chen Zhang, Zhan-Peng Huang, Hui Zhou, Mian-Bo Huang, Shu Zhang, Yue-Qin Chen and Liang-Hu Qu (2006). snoSeeker: an advanced computational package for screening of guide and orphan snoRNA genes in the human genome. Nucl Acids Res. 34: 5112-5123.
52. Yvan Saeys, Inaki Inza, Pedro Larranaga(2007). A review of feature selection techniques in-bioinformatics. Bioinformaitics. 23: 2507-2517.
53. Zhi John Lu, Kevin Y. Yip, Guilin Wang, Chong Shou, LaDeana W. Hillier, Ekta Khurana, Ashish Agarwal, Raymond Auerbach, Joel Rozowsky, Chao Cheng, Masaomi Kato, David M. Miller, Frank Slack, Michael Snyder, Robert H. Waterston, Valerie Reinke and Mark B. Gerstein (2011). Prediction and characterization of noncoding RNAs in C. elegans by integrating conservation, secondary structure, and high-throughput sequencing and array data. Genome Res. 21: 276-285.
54. Jasmina Ponjavic, Peter L. Oliver, Gerton Lunter, Chris P. Ponting. (2009) Genomic and Transcriptional Co-Localization of Protein-Coding and Long Non-Coding RNA Pairs in the Developing Brain. PLoS Genetics, 5: e100617.
55. Zheng Li, Min Liu, Li Zhang, Wenxia Zhang, Ge Gao, Zuoyan Zhu, Liping Wei, Qichang Fan and Manyuan Long. (2009) Detection of intergenic non-coding RNAs expressed in the main developmental stages in Drosophila melanogaster. Nucleic Acids Research, 37: 4308-4314.
56. Thomas Derrien, Rory Johnson, Giovanni Bussotti, Andrea Tanzer, Sarah Djebali, Hagen Tilgner, Gregory Guernec, David Martin, Angelika Merkel, David G. Knowles, Julien Lagarde, Lavanya Veeravalli, Xiaoan Ruan, Yijun Ruan, Timo Lassmann, Piero Carninci, James B. Brown, Leonard Lipovich, Jose M. Gonzalez, Mark Thomas, Carrie A. Davis, Ramin Shiekhattar, Thomas R. Gingeras, Tim J. Hubbard, Cedric Notredame, Jennifer Harrow and Roderic Guigo. (2012) The GENCODE v7 catalog of human long noncoding RNAs: Analysis of their gene structure, evolution, and expression. Genome Research, 22: 1775-1789.
57. Galina V. Glazko, Boris L. Zybailov, Igor B. Rogozin. (2012) Computational Prediction of Polycomb-Associated Long Non-Coding RNAs. PLOS ONE, 7(9): e44878.
58. Karen M. Chisholm, Yue Wan, Rui Li, Kelli D. Montgomery, Howard Y. Chang, Robert B. West. (2012) Detection of Long Non-Coding RNA in Archival Tissue: Correlation with Polycomb Protein Expression in Primary and Metastatic Breast Carcinoma. PLOS ONE, 7(10): e47998.
59. David Managadze, Alexander E. Lobkovsky, Yuri I. Wolf, Svetlana A. Shabalina, Igor B. Rogozin, Eugene V. Koonin. (2013) The Vast, Conserved Mammalian lincRNome. PLOS Computational Biology. 9(2): e1002917.
60. Susan Boerner, Karen M. McGinnis. (2012) Computational Identification and Functional Predictions of Long Noncoding RNA in Zea mays. PLoS ONE 7(8): e43047.
61. Ruqiang Liang, David J Bates, Eugenia Wang, (2009) Epigenetic Control of MicroRNA Expression and Aging. Current Genomics, 10(3): 184-193.