A combinational feature selection and ensemble neural network method for classification of gene expression data

BMC Bioinformatics

Volumn 5, Issue , 2004, Pages

  Liu, Bing ^a   Cui, Qinghua ^a   Jiang, Tianzi ^a   Ma, Songde ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ENSEMBLE NEURAL NETWORK; FEATURE SELECTION METHODS; GENE EXPRESSION DATA; GENE EXPRESSION PATTERNS; INTRINSIC CHARACTERISTICS; MICROARRAY EXPERIMENTS; SAMPLE CLASSIFICATION; TUMOR CLASSIFICATION;

DIAGNOSIS; DISEASES; GENE EXPRESSION; NEURAL NETWORKS; TUMORS;

CLASSIFICATION (OF INFORMATION);

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER RESEARCH; CLASSIFICATION; CONTROLLED STUDY; DATA ANALYSIS; DATA BASE; DNA MICROARRAY; GENE EXPRESSION SYSTEM; HUMAN; MARKER GENE; TUMOR CLASSIFICATION; VALIDATION PROCESS; ACUTE DISEASE; ACUTE LYMPHOBLASTIC LEUKEMIA; ARTIFICIAL INTELLIGENCE; B CELL LYMPHOMA; COLON TUMOR; COMPARATIVE STUDY; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; LARGE CELL LYMPHOMA; LUNG TUMOR; MALE; MYELOID LEUKEMIA; OVARY TUMOR; PREDICTIVE VALUE; PROCEDURES; PROSTATE TUMOR; VALIDATION STUDY;

ACUTE DISEASE; ARTIFICIAL INTELLIGENCE; COLONIC NEOPLASMS; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; LEUKEMIA, MYELOID; LUNG NEOPLASMS; LYMPHOMA, B-CELL; LYMPHOMA, LARGE B-CELL, DIFFUSE; MALE; NEURAL NETWORKS (COMPUTER); OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; OVARIAN NEOPLASMS; PRECURSOR CELL LYMPHOBLASTIC LEUKEMIA-LYMPHOMA; PREDICTIVE VALUE OF TESTS; PROSTATIC NEOPLASMS;

EID: 13244252329     PISSN: 14712105     EISSN: None     Source Type: Journal    
DOI: 10.1186/1471-2105-5-136     Document Type: Article

References (38)

1. David W, Galbraith: Global analysis of cell type-specific gene expression. Comp Funct Genom 2003,4:208-215.
2. Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, Eisen MB, Brown PO, Botstein D, Futcher B: Comprehensive identification of cell cycle-regulated genes of the yeast saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 1998, 9:3273-3297.
3. Nicholson TL, Olinger L, Chong K, Schoolnik G, Stephens RS: Global stage-specific gene regulation during the developmental cycle of chlamydia trachomatis. J Bacteriol 2003, 185:3179-3189.
4. Heller RA, Schena M, Chai A, Shalon D, Bedilion T, Gilmore J, Woolley DE, Davis RW: Discovery and analysis of inflammatory disease-related genes using cDNA microarrays. Proc Natl Acad Sci USA 1997,94:2150-2155.
5. Singh D, Febbo PG, Ross K, Jackson DG, Manola J, Ladd C, Tamayo P, Renshaw AA, D'Amico AV, Richie JP, Lander ES, Loda M, Kantoff PW, Golub TR, Sellers WR: Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 2002, 1:203-209.
6. Petricoin EF, Ardekani AM, Hitt BA, Levine PJ, Fusaro VA, Steinberg SM, Mills GB, Simone C, Fishman DA, Kohn EC, Liotta LA: Use of proteomic patterns in serum to identify ovarian cancer. Lancet 2002, 359:572-577.
7. Pomeroy SL, Tamayo P, Gaasenbeek M, Sturla LM, Angelo M, McLaughlin ME, Kim JY, Goumnerova LC, Black PM, Lau C, Allen JC, Zagzag D, Olson JM, Curran T, Wetmore C, Biegel JA, Poggio T, Mukherjee S, Rifkin R, Califano A, Stolovitzky G, Louis DN, Mesirov JP, Lander ES, Golub TR: Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature 2002, 415: 36-442.
8. Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RC, Gaasenbeek M, Angelo M, Reich M, Pinkus GS, Ray TS, Koval MA, Last KW, Norton A, Lister TA, Mesirov J, Neuberg DS, Lander ES, Aster JC, Golub TR: Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nature Medicine 2002, 8:68-74.
9. Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 1998, 95:14863-14868.
10. Cherepinsky V, Feng J, Rejali M, Mishra B: Shrinkage-based similarity metric for cluster analysis of microarray data. Proc Natl Acad Sci USA 2003, 100:9668-9673.
11. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES: Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 1999, 286: 31-537.
12. Khan J, Wei JS, Ringner M, Saal LH, Ladanyi M, Westermann F, Berthold F, Schwab M, Antonescu CR, Peterson C, Meltzer PS: Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature Medicine 2001, 7:673-679.
13. van't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, Linsley PS, Bernards R, Friend SH: Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002, 415:530-536.
14. 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. Proc Natl Acad Sci USA 1999, 96:6745-6750.
15. Armstrong SA, Staunton JE, Silverman LB, Pieters R, den Boer ML, Minden MD, Sallan SE, Lander ES, Golub TR, Korsmeyer SJ: MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nature Genetics 2002, 30: 1-47.
16. Yeoh EJ, Ross ME, Shurtleff SA, Williams WK, Patel D, Mahfouz R, Behm FG, Raimondi SC, Relling MV, Patel A, Cheng C, Campana D, Wilkins D, Zhou X, Li J, Liu H, Pui CH, Evans WE, Naeve C, Wong L, Downing JR: Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell 2002,1:133-143.
17. Gordon GJ, Jensen RV, Hsiao LL, Gullans SR, Blumenstock JE, Ramaswamy S, Richards WG, Sugarbaker DJ, Bueno R: Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma. Cancer Research 2002, 62:4963-4967.
18. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson J Jr, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Levy R, Wilson W, Grever MR, Byrd JC, Botstein D, Brown PO, Staudt LM: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000, 403:503-511.
19. DeRisi J, Penland L, Brown PO, Bittner ML, Meltzer PS, Ray M, Chen Y, Su YA, Trent JM: Use of a cDNA microarray to analyse gene expression patterns in human cancer. Nature Genetics 1996, 14:457-460.
20. Dudoit SJ, Fridlyand J, Speed T: Comparison of discrimination methods for the classification of tumors using gene expression data. J Am Stat Assoc 2002, 97:77-87.
21. Liu H, Li J, Wong L: A comparative study on feature selection and classification methods using gene expression profiles and proteomic Patterns. Genome Inform Ser Workshop Geonome Inform 2002, 13:51-60.
22. Jaeger J, Sengupta R, Ruzzo WL: Improved gene selection for classification of microarrays. Pac Symp Biocomput 2003:53-64.
23. O'Neill MC and Song L: Neural network analysis of lymphoma microarray data: prognosis and diagnosis near-perfect. BMC Bioinformatics 2003, 4:13.
24. Tan AC, Gilbert D: Ensemble machine learning on gene expression data for cancer classification. Applied Bioinformatics 2003, 2:S75-S83.
25. Cho SB, Won HH: Machine learning in DNA microarray analysis for cancer classification. Conferences in Research and Practice in Information Technology2003:19.
26. Long PM, Vega VB:Boosting and microarray data. Machine Learning 2002, 52:31-44.
27. Dettling M, Buhlmann P: Boosting for tumor classification with gene expression data. Bioinformatics 2003, 19: 061-1069.
28. Li J, Liu H, Ng SK, Wong L: Discovery of significant rules for classifying cancer diagnosis data. Bioinformatics 2003, 19(Suppl 2):ii93-ii102.
29. Ryu JW, Cho SB: Towards optimal feature and classifier for gene expression classification of cancer. Lecture Note in Artificial Intelligence2002, 2275:310-317.
30. Alter O, Brown PO, Botstein D: Singular value decomposition for genome-wide expression data processing and modeling. Proc Natl Acad Sci USA 2000, 97:10101-10106.
31. Speed T: Statistical analysis of gene expression microarray data. CRC Press 2003:190-197.
32. Wall ME, Dyck PA, Brettin TS: SVDMAN-singular value decomposition analysis of microarray data. Bioinformatics 2001, 17:566-568.
33. Raychaudhuri S, Stuart JM, Altman RB: Principle components analysis to summarize microarray experiments: Application to sporulation time series. Pac Symp Biocompu 2000: 452-463.
34. Devore JL: Probability and statistics for engineering and the sciences,. 4th edition. Ducbury Press; 1995.
35. Sharkey: On combining artificial neural nets. Connection Science 1996, 8:299-313.
36. Hansen L, Salomon P: Neural networks ensemble. Pattern Analysis and Machine Intelligence 1990, 12:993-1001.
37. Tumer K, Gosh J: Error correlation and error reduction in ensemble classifier. Connection Science 1996, 8:383-404.
38. Rosen B: Ensemble learning using decorrelated neural networks. Connection Science 1996, 8:373-384.