FiGS: A filter-based gene selection workbench for microarray data

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Hwang, Taeho ^a   Sun, Choong Hyun ^a   Yun, Taegyun ^a   Yi, Gwan Su ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ACCURACY; DIAGNOSTIC BIOMARKERS; METHODOLOGICAL STRATEGIES; MICROARRAY DATA SETS; PARALLEL-COMPUTING ENVIRONMENT; PARALLELIZED COMPUTING; SELECTION TECHNIQUES; WEB-BASED APPLICATIONS;

CLASSIFICATION (OF INFORMATION); DATA REDUCTION; DIAGNOSIS; OPTIMIZATION; PARALLEL ARCHITECTURES;

GENES;

ARTICLE; BIOLOGY; COMPUTER PROGRAM; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETIC DATABASE; METHODOLOGY;

COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; GENE EXPRESSION PROFILING; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SOFTWARE;

EID: 77249083227     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-50     Document Type: Article

References (23)

1. Medina I, Montaner D, Tarraga J, Dopazo J. Prophet, a web-based tool for class prediction using microarray data. Bioinformatics 2007, 23(3):390-391. 10.1093/bioinformatics/btl602, 17138587.
2. Statnikov A, Aliferis CF, Tsamardinos I, Hardin D, Levy S. A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. Bioinformatics 2005, 21(5):631-643. 10.1093/bioinformatics/bti033, 15374862.
3. Pochet NLMM, Janssens FAL, Smet FD, Marchal K, Suykens JAK, Moor BLRD. M@CBETH: a microarray classification benchmarking tool. Bioinformatics 2005, 21(14):3185-3186. 10.1093/bioinformatics/bti495, 15890742.
4. Saeys Y, Iñza I, Larrañaga P. A review of feature selection techniques in bioinformatics. Bioinformatics 2007, 23(19):2507-2517. 10.1093/bioinformatics/btm344, 17720704.
5. Liu H, Li J, Wong L. A Comparative Study on Feature Selection and Classification Methods Using Gene Expression Profiles and Proteomic Patterns. Genome Informatics 2002, 13:51-60.
6. Vapnik VN. Statistical learning theory 1998, New York, Wiley.
7. Breiman L. Random forests. Machine Learning 2001, 45:5-32.
8. Diaz-Uriarte R, de Andres SA. Gene selection and classification of microarray data using random forest. BMC Bioinformatics 2006, 7:3. 10.1186/1471-2105-7-3, 1363357, 16398926.
9. Statnikov A, Wang L, Aliferis CF. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification. BMC Bioinformatics 2008, 9:319. 10.1186/1471-2105-9-319, 2492881, 18647401.
10. Iñza I, Larrañaga P, Blanco R, Cerrolaza AJ. Filter versus wrapper gene selection approaches in DNA microarray domains. Artificial Intelligence in Medicine 2004, 31(2):91-103. 10.1016/j.artmed.2004.01.007, 15219288.
11. Potamias G, Koumakis L, Moustakis V. Gene Selection via Discretized Gene-Expression Profiles and Greedy Feature-Elimination. Lecture Notes in Computer Science 2004, 3025:256-266.
12. Efron B, Tibshirani R. Improvements on Cross-Validation: The .632+ Bootstrap Method. Journal of the American Statistical Association 1997, 92(438):548-560.
13. R Development Core Team R: A language and environment for statistical Computing 2009. R Foundation for statistical Computing, Vienna, Austria, ISBN 3-900051-07-0, R Development Core Team., http://www.R-project.org
14. Dimitriadou E, Hornik K, Leisch F, Meyer D, Weingessel A. e1071: Misc Functions of the Department of Statistics (e1071), TU Wien. , http://cran.r-project.org/web/packages/e1071/index.html
15. Liaw A, Wiener M. randomForest: Breiman and Cutler's random forests for classification and regression. , http://cran.r-project.org/web/packages/randomForest/index.html
16. Li N, Rossini AJ. rpvm: R interface to PVM (Parallel Virtual Machine). , http://cran.r-project.org/web/packages/rpvm/index.html
17. Tierney L, Rossini AJ, Li N, Sevcikova H. snow: Simple Network of Workstations. , http://cran.r-project.org/web/packages/snow/
18. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, et al. Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring. Science 1999, 286(5439):531-537. 10.1126/science.286.5439.531, 10521349.
19. Alon U, Barkai N, Notterman DA, Gish K, Ybarra S, Mack D, Levine AJ. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. The Proceedings of the National Academy of Sciences USA 1999, 96(12):6745-6750.
20. Singh D, Febbo PG, Ross K, Jackson DG, Manola J, Ladd C, Tamayo P, Renshaw AA, D'Amico AV, Richie JP, et al. Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 2002, 1(2):203-209. 10.1016/S1535-6108(02)00030-2, 12086878.
21. Ramaswamy S, Ross KN, Lander ES, Golub TR. A molecular signature of metastasis in primary solid tumors. Nature Genetics 2003, 33(1):49-54. 10.1038/ng1060, 12469122.
22. van't Veer LJ, Dai H, van be Vijver MJ, He YD, Hart AAM, Mao M, Peterse HL, de Kooy K, Marton MJ, Witteveen AT, et al. Gene expression profiling predicts clinical outome of breast cancer. Nature 2002, 415(6871):530-536. 10.1038/415530a, 11823860.
23. Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RCT, Gaasenbeek M, Angelo M, Reich M, Pinkus GS, et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nature Medicine 2002, 8(1):68-74. 10.1038/nm0102-68, 11786909.