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Volumn 8, Issue 5, 2011, Pages

mirExplorer: Detecting microRNAs from genome and next generation sequencing data using the adaboost method with transition probability matrix and combined features

Author keywords

Adaptive boosting; microRNA; Next generation sequencing technology; SMOTE; Transition probability matrix

Indexed keywords

MICRORNA;

EID: 80052792180     PISSN: 15476286     EISSN: 15558584     Source Type: Journal    
DOI: 10.4161/rna.8.5     Document Type: Article
Times cited : (26)

References (42)
  • 2
    • 34447107760 scopus 로고    scopus 로고
    • The Mirtron Pathway Generates microRNA-Class Regulatory RNAs in Drosophila
    • DOI 10.1016/j.cell.2007.06.028, PII S0092867407007957
    • Okamura K, Hagen JW, Duan H, Tyler DM, Lai EC. The mirtron pathway generates microRNA-class regulatory RNAs in Drosophila. Cell 2007; 130:89-100. (Pubitemid 47031325)
    • (2007) Cell , vol.130 , Issue.1 , pp. 89-100
    • Okamura, K.1    Hagen, J.W.2    Duan, H.3    Tyler, D.M.4    Lai, E.C.5
  • 3
    • 1842608548 scopus 로고    scopus 로고
    • MicroRNA precursors in motion: Exportin-5 mediates their nuclear export
    • DOI 10.1016/j.tcb.2004.02.006, PII S0962892404000534
    • Kim VN. MicroRNA precursors in motion: exportin-5 mediates their nuclear export. Trends Cell Biol 2004; 14:156-9. (Pubitemid 38447114)
    • (2004) Trends in Cell Biology , vol.14 , Issue.4 , pp. 156-159
    • Kim, V.N.1
  • 5
  • 6
    • 35348821616 scopus 로고    scopus 로고
    • MicroRNAs in vertebrate physiology and human disease
    • Chang TC, Mendell JT. microRNAs in vertebrate physiology and human disease. Annu Rev Genomics Hum Genet 2007; 8:215-39.
    • (2007) Annu Rev Genomics Hum Genet , vol.8 , pp. 215-239
    • Chang, T.C.1    Mendell, J.T.2
  • 7
    • 22144461002 scopus 로고    scopus 로고
    • miRNAs, cancer, and stem cell division
    • DOI 10.1016/j.cell.2005.06.036, PII S0092867405006550
    • Croce CM, Calin GA. miRNAs, cancer and stem cell division. Cell 2005; 122:6-7. (Pubitemid 40977933)
    • (2005) Cell , vol.122 , Issue.1 , pp. 6-7
    • Croce, C.M.1    Calin, G.A.2
  • 8
    • 0347444723 scopus 로고    scopus 로고
    • MicroRNAs: Genomics, biogenesis, mechanism and function
    • Bartel DP. MicroRNAs: genomics, biogenesis, mechanism and function. Cell 2004; 116:281-97.
    • (2004) Cell , vol.116 , pp. 281-297
    • Bartel, D.P.1
  • 12
    • 24644476482 scopus 로고    scopus 로고
    • MicroRNA identification based on sequence and structure alignment
    • DOI 10.1093/bioinformatics/bti562
    • Wang X, Zhang J, Li F, Gu J, He T, Zhang X, et al. MicroRNA identification based on sequence and structure alignment. Bioinformatics 2005; 21:3610-4. (Pubitemid 41264095)
    • (2005) Bioinformatics , vol.21 , Issue.18 , pp. 3610-3614
    • Wang, X.1    Zhang, J.2    Li, F.3    Gu, J.4    He, T.5    Zhang, X.6    Li, Y.7
  • 13
    • 30344447264 scopus 로고    scopus 로고
    • Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine
    • Xue C, Li F, He T, Liu GP, Li Y, Zhang X. Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics 2005; 6:310.
    • (2005) BMC Bioinformatics , vol.6 , pp. 310
    • Xue, C.1    Li, F.2    He, T.3    Liu, G.P.4    Li, Y.5    Zhang, X.6
  • 14
    • 34447309058 scopus 로고    scopus 로고
    • De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures
    • DOI 10.1093/bioinformatics/btm026
    • Ng KLS, Mishra SK. De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures. Bioinformatics 2007; 23:1321-30. (Pubitemid 47050513)
    • (2007) Bioinformatics , vol.23 , Issue.11 , pp. 1321-1330
    • Ng, K.L.S.1    Mishra, S.K.2
  • 15
    • 64549116289 scopus 로고    scopus 로고
    • microPred: effective classification of pre-miRNAs for human miRNA gene prediction
    • Batuwita R, Palade V. microPred: effective classification of pre-miRNAs for human miRNA gene prediction. Bioinformatics 2009; 25:989-95.
    • (2009) Bioinformatics , vol.25 , pp. 989-995
    • Batuwita, R.1    Palade, V.2
  • 16
    • 34547596338 scopus 로고    scopus 로고
    • MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features
    • Jiang P, Wu H, Wang W, Ma W, Sun X, Lu Z. MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids Res 2007; 35:339-44.
    • (2007) Nucleic Acids Res , vol.35 , pp. 339-344
    • Jiang, P.1    Wu, H.2    Wang, W.3    Ma, W.4    Sun, X.5    Lu, Z.6
  • 17
    • 33747814183 scopus 로고    scopus 로고
    • ProMiR II: A web server for the probabilistic prediction of clustered, nonclustered, conserved and nonconserved microRNAs
    • Nam JW, Kim J, Kim SK, Zhang BT. ProMiR II: a web server for the probabilistic prediction of clustered, nonclustered, conserved and nonconserved microRNAs. Nucleic Acids Res 2006; 34:455-8.
    • (2006) Nucleic Acids Res , vol.34 , pp. 455-458
    • Nam, J.W.1    Kim, J.2    Kim, S.K.3    Zhang, B.T.4
  • 18
    • 79952200065 scopus 로고    scopus 로고
    • Utilization of SSCprofiler to predict a new miRNA gene
    • Oulas A, Poirazi P. Utilization of SSCprofiler to predict a new miRNA gene. Methods Mol Biol 676:243-52.
    • Methods Mol Biol , vol.676 , pp. 243-252
    • Oulas, A.1    Poirazi, P.2
  • 19
    • 67249093200 scopus 로고    scopus 로고
    • Prediction of novel microRNA genes in cancer-associated genomic regions- A combined computational and experimental approach
    • Oulas A, Boutla A, Gkirtzou K, Reczko M, Kalantidis K, Poirazi P. Prediction of novel microRNA genes in cancer-associated genomic regions - a combined computational and experimental approach. Nucleic Acids Res 2009; 37:3276-87.
    • (2009) Nucleic Acids Res , vol.37 , pp. 3276-3287
    • Oulas, A.1    Boutla, A.2    Gkirtzou, K.3    Reczko, M.4    Kalantidis, K.5    Poirazi, P.6
  • 20
    • 77951652329 scopus 로고    scopus 로고
    • New syntax to describe local continuous structure-sequence information for recognizing new pre-miRNAs
    • Wang M, Song X, Han P, Li W, Jiang B. New syntax to describe local continuous structure-sequence information for recognizing new pre-miRNAs. J Theor Biol 2010; 264:578-84.
    • (2010) J Theor Biol , vol.264 , pp. 578-584
    • Wang, M.1    Song, X.2    Han, P.3    Li, W.4    Jiang, B.5
  • 22
    • 39649117755 scopus 로고    scopus 로고
    • The impact of next-generation sequencing technology on genetics
    • Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet 2008; 24:133-41.
    • (2008) Trends Genet , vol.24 , pp. 133-141
    • Mardis, E.R.1
  • 23
    • 53649100100 scopus 로고    scopus 로고
    • The development and impact of 454 sequencing
    • Rothberg JM, Leamon JH. The development and impact of 454 sequencing. Nat Biotechnol 2008; 26:1117-24.
    • (2008) Nat Biotechnol , vol.26 , pp. 1117-1124
    • Rothberg, J.M.1    Leamon, J.H.2
  • 25
    • 16344396421 scopus 로고    scopus 로고
    • Accurate identification of alternatively spliced exons using support vector machine
    • DOI 10.1093/bioinformatics/bti132
    • Dror G, Sorek R, Shamir R. Accurate identification of alternatively spliced exons using support vector machine. Bioinformatics 2005; 21:897-901. (Pubitemid 40467908)
    • (2005) Bioinformatics , vol.21 , Issue.7 , pp. 897-901
    • Dror, G.1    Sorek, R.2    Shamir, R.3
  • 26
    • 0028249154 scopus 로고
    • Prediction of RNA secondary structure by energy minimization
    • Zuker M. Prediction of RNA secondary structure by energy minimization. Methods Mol Biol 1994; 25:267-94.
    • (1994) Methods Mol Biol , vol.25 , pp. 267-294
    • Zuker, M.1
  • 28
    • 0031211090 scopus 로고    scopus 로고
    • A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting*
    • Freund Y, Schapire RE. A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting*. J Comput Syst Sci 1997; 55:21.
    • (1997) J Comput Syst Sci , vol.55 , pp. 21
    • Freund, Y.1    Schapire, R.E.2
  • 29
    • 33748947459 scopus 로고    scopus 로고
    • Under-Sampling Approaches for Improving Prediction of the Minority Class in an Imbalanced Dataset
    • Yen SJ, Lee YS. Under-Sampling Approaches for Improving Prediction of the Minority Class in an Imbalanced Dataset Lecture Notes in Control and Information Sciences 2006; 344:10.
    • (2006) Lecture Notes in Control and Information Sciences , vol.344 , pp. 10
    • Yen, S.J.1    Lee, Y.S.2
  • 30
    • 0023890867 scopus 로고
    • Measuring the accuracy of diagnostic systems
    • Swets JA. Measuring the accuracy of diagnostic systems. Science 1988; 240:1285-93.
    • (1988) Science , vol.240 , pp. 1285-1293
    • Swets, J.A.1
  • 31
    • 54349089811 scopus 로고    scopus 로고
    • Identification of microRNA precursors with support vector machine and string kernel
    • Xu JH, Li F, Sun QF. Identification of microRNA precursors with support vector machine and string kernel. Genomics Proteomics Bioinformatics 2008; 6:121-8.
    • (2008) Genomics Proteomics Bioinformatics , vol.6 , pp. 121-128
    • Xu, J.H.1    Li, F.2    Sun, Q.F.3
  • 33
    • 0035800521 scopus 로고    scopus 로고
    • A cellular function for the RNA-interference enzyme dicer in the maturation of the let-7 small temporal RNA
    • DOI 10.1126/science.1062961
    • Hutvagner G, McLachlan J, Pasquinelli AE, Balint E, Tuschl T, Zamore PD. A cellular function for the RNA-interference enzyme Dicer in the maturation of the let-7 small temporal RNA. Science 2001; 293:834-8. (Pubitemid 32743968)
    • (2001) Science , vol.293 , Issue.5531 , pp. 834-838
    • Hutvagner, G.1    McLachlan, J.2    Pasquinelli, A.E.3    Balint, E.4    Tuschl, T.5    Zamore, P.D.6
  • 34
    • 11244251011 scopus 로고    scopus 로고
    • Plant and animal microRNAs: Similarities and differences
    • DOI 10.1007/s10142-005-0145-2
    • Millar AA, Waterhouse PM. Plant and animal microRNAs: similarities and differences. Funct Integr Genomics 2005; 5:129-35. (Pubitemid 40823254)
    • (2005) Functional and Integrative Genomics , vol.5 , Issue.3 , pp. 129-135
    • Millar, A.A.1    Waterhouse, P.M.2
  • 35
    • 17844391015 scopus 로고    scopus 로고
    • Structural RNA has lower folding energy than random RNA of the same dinucleotide frequency
    • DOI 10.1261/rna.7220505
    • Clote P, Ferre F, Kranakis E, Krizanc D. Structural RNA has lower folding energy than random RNA of the same dinucleotide frequency. RNA 2005; 11:578-91. (Pubitemid 40594326)
    • (2005) RNA , vol.11 , Issue.5 , pp. 578-591
    • Clote, P.1    Ferre, F.2    Kranakis, E.3    Krizanc, D.4
  • 38
    • 0036081355 scopus 로고    scopus 로고
    • Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
    • Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 2002; 30:207-10. (Pubitemid 34679544)
    • (2002) Nucleic Acids Research , vol.30 , Issue.1 , pp. 207-210
    • Edgar, R.1    Domrachev, M.2    Lash, A.E.3
  • 40
    • 19044399340 scopus 로고    scopus 로고
    • A new approach in the BCI research based on fractal dimension as feature and Adaboost as classifier
    • DOI 10.1088/1741-2560/1/4/004, PII S1741256004776168
    • Boostani R, Moradi MH. A new approach in the BCI research based on fractal dimension as feature and Adaboost as classifier. J Neural Eng 2004; 1:212-7. (Pubitemid 41079655)
    • (2004) Journal of Neural Engineering , vol.1 , Issue.4 , pp. 212-217
    • Boostani, R.1    Moradi, M.H.2
  • 41
    • 68349147943 scopus 로고    scopus 로고
    • Prediction of interaction between small molecule and enzyme using adaboost
    • Niu B, Jin Y, Lu L, Fen K, Gu L, He Z, et al. Prediction of interaction between small molecule and enzyme using AdaBoost. Mol Divers 2009; 13:313-20.
    • (2009) Mol Divers , vol.13 , pp. 313-320
    • Niu, B.1    Jin, Y.2    Lu, L.3    Fen, K.4    Gu, L.5    He, Z.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.