A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs

Osong Public Health and Research Perspectives

Volumn 5, Issue 5, 2014, Pages 279-285

  Li, Feifei ^a   Piao, Minghao ^a   Piao, Yongjun ^a   Li, Meijing ^a   Ryu, Keun Ho ^a  

^a Chungbuk National University   (South Korea)

Author keywords

Cancer classification; Feature selection; Low ranking miRNAs; MiRNA expression profile

Indexed keywords

MICRORNA;

ACCURACY; ARTICLE; B CELL LEUKEMIA; BAYES THEOREM; CANCER CLASSIFICATION; CHI SQUARE TEST; CHRONIC LYMPHATIC LEUKEMIA; COLON CANCER; CONTROLLED STUDY; CORRELATION COEFFICIENT; DECISION TREE; DEREGULATION; HUMAN; K NEAREST NEIGHBOR; PANCREAS CANCER; SUPPORT VECTOR MACHINE; T CELL LEUKEMIA; UTERUS CANCER;

EID: 84922523410     PISSN: 22109099     EISSN: 22336052     Source Type: Journal    
DOI: 10.1016/j.phrp.2014.08.004     Document Type: Article

References (16)

1. Mraz M., Pospisilova S. MicroRNAs in chronic lymphocytic leukaemia. From causality to associations and back. Exp Rev Hematol 2012 Dec, 5(6):579-581.
2. He L., Thomson J.M., Hemann M.T., et al. A microRNA polycistron as a potential human oncogene. Nature 2005 Jun, 435(7043):828-833.
3. Mraz M., Pospisilova S., Malinova K., et al. MicroRNAs in chronic lymphocytic leukemia pathogenesis and disease subtypes. Leuk Lymphoma 2009 Mar, 50(3):506-509.
4. Lee R.C., Feinbaum R.L., Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 1993 Dec, 75(5):843-854.
5. Cunningham J.M., Oberg A.N., Borralho P.M., et al. Evaluation of a new high-dimensional miRNA profiling platform. BMC Med Genomics 2009 Aug, 2(57):1-14.
6. Lu J., Getz G., Miska E.A., et al. MicroRNA expression profiles classify human cancers. Nature Jun 2005, 435(7043):834-838.
7. Zheng Y., Chee K.K. Cancer classification with microRNA expression patterns found by an information theory approach. J Computer 2006 Aug, 1(5):30-39.
8. Xu R., Xu J., Wunsch D.C. MicroRNA expression profile based cancer classification using Default ARTMAP. Neural Networks 2009 Jul-Aug, 22(5-6):774-780.
9. Kim K.J., Cho S.B. Exploring features and classifiers to classify microRNA expression profiles of human cancer. Neural Information Processing 2012, 6444:234-241.
10. Moller H.G., Rasmussen A.P., Andersen H.H., et al. A systematic review of microRNA in glioblastoma multiforme: micro-modulators in the mesenchymal mode of migration and invasion. Mol Neurobiol 2013 Feb, 47(1):131-144.
11. Hall M. Correlation-based feature selection for machine learning [PhD Thesis] 1999, Department of Computer Science, Waikato University, New Zealand.
12. Chang C.C., Lin C.J. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent System and Technology 2011 Apr, (2):1-27.
13. Xu J.H., Li F., Sun Q.F. Identification of microRNA precursors with support vector machine and string kernel. Genomics Proteomics Bioinformatics 2008 Jun, 6(2):121-128.
14. Campos L.M., Cano A., Castellano J.G., et al. Bayesian networks classifiers for gene-expression data 2011 Nov, 1200-1206. 11th International Conference on Intelligent Systems Design and Applications (ISDA).
15. Mishra A.K., Chandrasekharan H. Analysis and classification of plant microRNAs using decision tree based approach. ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India 2014, vol. II:105-110.
16. Jordan M.I. On discriminative vs. generative classifiers: a comparison of logistic regression and naive Bayes. Advances in neural information processing systems 2002, 14:841-848.