Bartel DP: MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 2004, 116(2):281–297. 10.1016/S0092-8674(04)00045-5
Article
CAS
PubMed
Google Scholar
Lee RC, Feinbaum RL, Ambros V: The C-Elegans Heterochronic Gene Lin-4 Encodes Small RNAs with Antisense Complementarity to Lin-14. Cell 1993, 75(5):843–854. 10.1016/0092-8674(93)90529-Y
Article
CAS
PubMed
Google Scholar
Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, Horvitz HR, Ruvkun G: The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 2000, 403(6772):901–906. 10.1038/35002607
Article
CAS
PubMed
Google Scholar
Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ: miRBase: tools for microRNA genomics. Nucleic Acids Res 2008, 36: D154-D158. 10.1093/nar/gkm952
Article
PubMed Central
CAS
PubMed
Google Scholar
Chen PY, Manninga H, Slanchev K, Chien MC, Russo JJ, Ju JY, Sheridan R, John B, Marks DS, Gaidatzis D, et al.: The developmental miRNA profiles of zebrafish as determined by small RNA cloning. Genes & Development 2005, 19(11):1288–1293. 10.1101/gad.1310605
Article
CAS
Google Scholar
Berezikov E, Cuppen E, Plasterk RHA: Approaches to microRNA discovery. Nature Genetics 2006, 38: S2-S7. 10.1038/ng1794
Article
CAS
PubMed
Google Scholar
Boffelli D, McAuliffe J, Ovcharenko D, Lewis KD, Ovcharenko I, Pachter L, Rubin EM: Phylogenetic shadowing of primate sequences to find functional regions of the human genome. Science 2003, 299(5611):1391–1394. 10.1126/science.1081331
Article
CAS
PubMed
Google Scholar
Grad Y, Aach J, Hayes GD, Reinhart BJ, Church GM, Ruvkun G, Kim J: Computational and experimental identification of C-elegans microRNAs. Molecular Cell 2003, 11(5):1253–1263. 10.1016/S1097-2765(03)00153-9
Article
CAS
PubMed
Google Scholar
Bentwich I, Avniel A, Karov Y, Aharonov R, Gilad S, Barad O, Barzilai A, Einat P, Einav U, Meiri E, et al.: Identification of hundreds of conserved and nonconserved human microRNAs. Nature Genetics 2005, 37(7):766–770. 10.1038/ng1590
Article
CAS
PubMed
Google Scholar
Berezikov E, Guryev V, Belt J, Wienholds E, Plasterk RHA, Cuppen E: Phylogenetic shadowing and computational identification of human microRNA genes. Cell 2005, 120(1):21–24. 10.1016/j.cell.2004.12.031
Article
CAS
PubMed
Google Scholar
Sewer A, Paul N, Landgraf P, Aravin A, Pfeffer S, Brownstein MJ, Tuschl T, van Nimwegen E, Zavolan M: Identification of clustered microRNAs using an ab initio prediction method. BMC Bioinformatics 2005., 6: 10.1186/1471-2105-6-267
Google Scholar
Xue CH, Li F, He T, Liu GP, Li YD, Zhang XG: Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics 2005., 6: 10.1186/1471-2105-6-310
Google Scholar
Brameier M, Wiuf C: Ab initio identification of human microRNAs based on structure motifs. BMC Bioinformatics 2007., 8: 10.1186/1471-2105-8-478
Google Scholar
Kwang Loong S, Mishra SK: De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures. Bioinformatics 2007, 23(11):1321–1330. 10.1093/bioinformatics/btm026
Article
Google Scholar
Chang DTH, Wang CC, Chen JW: Using a kernel density estimation based classifier to predict species-specific microRNA precursors. BMC Bioinformatics 2008., 9: 10.1186/1471-2105-9-432
Google Scholar
Schultes EA, Hraber PT, LaBean TH: Estimating the contributions of selection and self-organization in RNA secondary structure. J Mol Evol 1999, 49(1):76–83. 10.1007/PL00006536
Article
CAS
PubMed
Google Scholar
Zhang BH, Pan XP, Cox SB, Cobb GP, Anderson TA: Evidence that miRNAs are different from other RNAs. Cell Mol Life Sci 2006, 63(2):246–254. 10.1007/s00018-005-5467-7
Article
CAS
PubMed
Google Scholar
Freyhult E, Gardner PP, Moulton V: A comparison of RNA folding measures. BMC Bioinformatics 2005., 6:
Google Scholar
Gan HH, Fera D, Zorn J, Shiffeldrim N, Tang M, Laserson U, Kim N, Schlick T: RAG: RNA-As-Graphs database - concepts, analysis, and features. Bioinformatics 2004, 20(8):1285–1291. 10.1093/bioinformatics/bth084
Article
CAS
PubMed
Google Scholar
Nam JW, Shin KR, Han JJ, Lee Y, Kim VN, Zhang BT: Human microRNA prediction through a probabilistic co-learning model of sequence and structure. Nucleic Acids Res 2005, 33(11):3570–3581. 10.1093/nar/gki668
Article
PubMed Central
CAS
PubMed
Google Scholar
Terai G, Komori T, Asai K, Kin T: miRRim: A novel system to find conserved miRNAs with high sensitivity and specificity. RNA-a Publication of the RNA Society 2007, 13(12):2081–2090.
Article
CAS
Google Scholar
Yang YC, Wang YP, Li KB: MiRTif: a support vector machine-based microRNA target interaction filter. BMC Bioinformatics 2008., 9:
Google Scholar
Batuwita R, Palade V: microPred: effective classification of pre-miRNAs for human miRNA gene prediction. Bioinformatics 2009, 25(8):989–995. 10.1093/bioinformatics/btp107
Article
CAS
PubMed
Google Scholar
Jain AK, Duin RPW, Mao JC: Statistical pattern recognition: A review. IEEE Transactions on Pattern Analysis and Machine Intelligence 2000, 22(1):4–37. 10.1109/34.824819
Article
Google Scholar
Huang LT, Gromiha MM, Ho SY: iPTREE-STAB: interpretable decision tree based method for predicting protein stability changes upon mutations. Bioinformatics 2007, 23(10):1292–1293. 10.1093/bioinformatics/btm100
Article
CAS
PubMed
Google Scholar
Zhou XF, Ruan JH, Wang GD, Zhang WX: Characterization and identification of microRNA core promoters in four model species. PLoS Comput Biol 2007, 3(3):412–423. 10.1371/journal.pcbi.0030037
Article
CAS
Google Scholar
Ho SY, Hsieh CH, Chen HM, Huang HL: Interpretable gene expression classifier with an accurate and compact fuzzy rule base for microarray data analysis. Biosystems 2006, 85(3):165–176. 10.1016/j.biosystems.2006.01.002
Article
CAS
PubMed
Google Scholar
Zhou GD: Recognizing names in biomedical texts using mutual information independence model and SVM plus sigmoid. Int J Med Inf 2006, 75(6):456–467. 10.1016/j.ijmedinf.2005.06.012
Article
CAS
Google Scholar
Hsieh C-H, Chang DT-H, Oyang Y-J: Data Classification with a Generalized Gaussian Components based Density Estimation Algorithm. International Joint Conference on Neural Networks. Atlanta, Georgia 2009.
Google Scholar
Ritchie W, Legendre M, Gautheret D: RNA stem-loops: To be or not to be cleaved by RNAse III. RNA 2007, 13(4):457–462. 10.1261/rna.366507
Article
PubMed Central
CAS
PubMed
Google Scholar
Chang DTH, Oyang YJ, Lin JH: MEDock: a web server for efficient prediction of ligand binding sites based on a novel optimization algorithm. Nucleic Acids Res 2005, 33: W233-W238. 10.1093/nar/gki586
Article
PubMed Central
CAS
PubMed
Google Scholar
Oyang YJ, Hwang SC, Ou YY, Chen CY, Chen ZW: Data classification with radial basis function networks based on a novel kernel density estimation algorithm. IEEE Transactions on Neural Networks 2005, 16(1):225–236. 10.1109/TNN.2004.836229
Article
PubMed
Google Scholar
Han LY, Cai CZ, Lo SL, Chung MCM, Chen YZ: Prediction of RNA-binding proteins from primary sequence by a support vector machine approach. RNA 2004, 10(3):355–368. 10.1261/rna.5890304
Article
PubMed Central
PubMed
Google Scholar
Dror G, Sorek R, Shamir R: Accurate identification of alternatively spliced exons using support vector machine. Bioinformatics 2005, 21(7):897–901. 10.1093/bioinformatics/bti132
Article
CAS
PubMed
Google Scholar
Quinlan JR: C4.5: Programs for Machine Learning. San Francisco: Morgan Kaufmann; 1993.
Google Scholar
Cohen WW: Fast effective rule induction. International Conference on Machine Learning 1995 1995, 115–123.
Google Scholar
Wilcoxon F: Individual Comparisons by Ranking Methods. Biometrics Bulletin 1945, 1(6):80–83. 10.2307/3001968
Article
Google Scholar
Hogg RV, Tanis EA: Probability and statistical inference. 7th edition. Upper Saddle River, NJ: Pearson Prentice Hall; 2006.
Google Scholar
Seffens W, Digby D: mRNAs have greater negative folding free energies than shuffled or codon choice randomized sequences. Nucleic Acids Res 1999, 27(7):1578–1584. 10.1093/nar/27.7.1578
Article
PubMed Central
CAS
PubMed
Google Scholar
Moulton V, Zuker M, Steel M, Pointon R, Penny D: Metrics on RNA secondary structures. J Comput Biol 2000, 7(1–2):277–292. 10.1089/10665270050081522
Article
CAS
PubMed
Google Scholar
Fera D, Kim N, Shiffeldrim N, Zorn J, Laserson U, Gan HH, Schlick T: RAG: RNA-As-Graphs web resource. BMC Bioinformatics 2004., 5: 10.1186/1471-2105-5-88
Google Scholar
Larsen RJ, Marx ML: An Introduction to Mathematical Statistics and Its Applications. 3rd edition. Prentice Hall; 2005.
Google Scholar
Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ: miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 2006, 34: D140-D144. 10.1093/nar/gkj112
Article
PubMed Central
CAS
PubMed
Google Scholar
Pruitt KD, Maglott DR: RefSeq and LocusLink: NCBI gene-centered resources. Nucleic Acids Res 2001, 29(1):137–140. 10.1093/nar/29.1.137
Article
PubMed Central
CAS
PubMed
Google Scholar
Karolchik D, Baertsch R, Diekhans M, Furey TS, Hinrichs A, Lu YT, Roskin KM, Schwartz M, Sugnet CW, Thomas DJ, et al.: The UCSC Genome Browser Database. Nucleic Acids Res 2003, 31(1):51–54. 10.1093/nar/gkg129
Article
PubMed Central
CAS
PubMed
Google Scholar
Hofacker IL: Vienna RNA secondary structure server. Nucleic Acids Res 2003, 31(13):3429–3431. 10.1093/nar/gkg599
Article
PubMed Central
CAS
PubMed
Google Scholar
Chang CC, Lin CJ: LIBSVM: a library for support vector machines.2001. [http://www.csie.ntu.edu.tw/~cjlin/libsvm]
Google Scholar