Finding rule groups to classify high dimensional gene expression datasets

Computational Biology and Chemistry

Volumn 33, Issue 1, 2009, Pages 108-113

  An, Jiyuan ^a   Chen, Yi Ping Phoebe ^a,b  

^a DEAKIN UNIVERSITY   (Australia)

^b Australian Government Australian Research Council   (Australia)

Author keywords

Classification; Gene expression datasets; Microarray data analysis

Indexed keywords

BIOACTIVITY; BIOINFORMATICS; DATA REDUCTION; GENE EXPRESSION; GENES; GROUP TECHNOLOGY; LEARNING SYSTEMS; ROBOT LEARNING;

CLASSIFICATION; CLASSIFICATION ALGORITHMS; CLASSIFICATION APPROACHES; DATA SETS; GENE EXPRESSION DATASETS; HIGH DIMENSIONALITIES; MACHINE LEARNING METHODS; MACHINE LEARNINGS; MICROARRAY DATA ANALYSIS; MICROARRAY DATA SETS; MICROARRAY DATUMS; NORMAL TISSUES; QUANTITATIVE INFORMATIONS; ROBUST ALGORITHMS; TRANSCRIPTION PROFILES;

TRANSCRIPTION;

ALGORITHM; ARTICLE; BIOLOGY; DNA MICROARRAY; GENE EXPRESSION;

ALGORITHMS; COMPUTATIONAL BIOLOGY; GENE EXPRESSION; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 57749192475     PISSN: 14769271     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiolchem.2008.07.031     Document Type: Article

References (22)

1. Allison D.B., et al. Microarray data analysis: from disarray to consolidation and consensus. Nat. Rev. Genet. (2006) 55-65
2. Alon U., Barkai N., Notterman D.A., Gish K., Ybarra S., Mack D., and Levine A.J. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc. Natl Acad. Sci. U.S.A. 96 (1999) 6745-6750
3. An J., Chen Y.P.P., and Chen H. DDR: an index method for large time series datasets. Inform. Syst. 30 (2005) 333-348
4. An J., and Chen Y.P.P. Another inductive algorithm. Lect. Notes Artif. Intellig. 3682 (2005) 37-44
5. Asyali M.H., et al. Gene expression profile classification: a review. Curr. Bioinformatics 1 (2006) 55-73
6. Bayardo, R.J., 1998. Efficiently mining long patterns from databases. 17th ACM SIGMOD International Conference on Management of Data, 85-93.
7. Bhattacharjee A., et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl Acad. Sci. U.S.A. 98 (2001) 13790-13795
8. Chen Q., Chen Y.P.P., and Zhang C. Detecting inconsistency in biological molecular databases using ontology. Data Min. Knowl. Discov. 15 2 (2007) 275-296
9. Clark, P., Boswell, R., 1991. Rule induction with CN2: some recent improvements. Mach. Learn. EWSL-91, 151-163.
10. Fayyad U.M., and Irani K.B. Multi-interval discretization of continuous-valued attributes for classification learning. IJCAI 93 (1993) 1022-1027
11. Golub T.R., et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286 (1999) 531-537
12. Khan J., et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat. Med. 7 (2001) 673-679
13. Knapp K., and Chen Y.P.P. An evaluation of contemporary hidden markov model genefinders with a predicted exon taxonomy. Nucleic Acids Research 35 (2007) 317-324
14. Mann S., Li J., and Chen Y.P.P. A pHMM-ANN based discriminative approach to promoter identification in prokaryote genomic contexts. Nucleic Acids Res. 35 e12 (2007) 1-7
15. Mitchell T. Machine Learning (1997), McGraw Hill
16. Mramor M., Leban G., Demsar J., and Zupan B. Visualization-based cancer microarray data classification analysis. Bioinformatics 23 16 (2007) 2147-2154
17. Nahar J., Chen Y.P.P., and Ali S. Kernel based naive bayes classifier for breast cancer prediction. J. Biol. Syst. 15 1 (2007) 17-25
18. Pham T.D., et al. Analysis of microarray gene expression data. Curr. Bioinformatics 1 (2006) 37-53
19. Quinlan J.R. Induction of decision trees. Mach. Learn. 1 1 (1986) 81-106
20. Rymon, R., 1992. Search through systematic set enumeration. Proceedings KR'92, 268-275.
21. Shipp M.A., et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat. Med. 8 (2002) 68-74
22. Yang, Y., Pedersen, J.P., 1997. A comparative study on feature selection in text categorization. Proceedings of the Fourteenth International Conference on Machine Learning (ICML'97), 412-420.