Pathway activity transformation for multi-class classification of lung cancer datasets

Neurocomputing

Volumn 165, Issue , 2015, Pages 81-89

  Engchuan, Worrawat ^a   Chan, Jonathan H ^a  

^a KING MONGKUT'S UNIVERSITY OF TECHNOLOGY THONBURI   (Thailand)

Author keywords

ANOVA; Lung cancer; Multi class classification; Multilayer perceptron; Pathway activity transformation; Support Vector Machine

Indexed keywords

ANALYSIS OF VARIANCE (ANOVA); BIOLOGICAL ORGANS; CLASSIFIERS; DISEASES; GENE EXPRESSION; LEARNING SYSTEMS; METADATA; MULTILAYER NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

CLASSIFICATION POWER; CLASSIFICATION RESULTS; DISEASE CLASSIFICATION; LUNG CANCER; MULTI-CLASS CLASSIFICATION; PATHWAY ACTIVITIES; THREE FOLD CROSS VALIDATION; TRANSFORMATION METHODS;

CLASSIFICATION (OF INFORMATION);

ANALYSIS OF VARIANCE; ARTICLE; CANCER CLASSIFICATION; GENE EXPRESSION; GENETIC MARKER; HUMAN; INTERMETHOD COMPARISON; LUNG CANCER; MICROARRAY ANALYSIS; PATHWAY ACTIVITY TRANSFORMATION METHOD; PERCEPTRON; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SUPPORT VECTOR MACHINE; VALIDATION STUDY;

EID: 84929953593     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.08.096     Document Type: Article

References (25)

1. American Cancer Society, Cancer Facts & Figures 2011, Atlanta. Am. Cancer Soc., 2011.
2. W. Laureen, B.C. Goh, An overview of cancer trends in Asia, Innovationmagazine.com., 2012.
3. Cornfield J., Haenszel W., Hammond E.C., Lilienfield A.M., Shimkin M.B., Wynder E.L. Smoking and lung cancer: recent evidence and a discussion of some question. Int. J. Epidemiol. 2009, 38:1175-1191.
4. Splitz M.R., Wei Q., Dong Q., Amos C.I., Wu X. Genetic susceptibility to lung cancer: the role of DNA damage and repair. Cancer Epidemol. Biomark. Prev. 2003, 12:689-698.
5. C.S. Melissa, LungCancer, Medicine.net, 2011.
6. Clifton F.M., Carolyn M.D. Regional lymph node classification for lung cancer staging. CHEST 1997, 111:1718-1723.
7. Clifton F.M. Revisions in the international system for staging lung cancer. CHEST 1997, 111:1710-1717.
8. Jeffrey A.T., Hagen J.A., Carpenter C.L., Laird-Offringa I.A. DNA methylation analysis: a powerful new tool for lung cancer diagnosis. Oncogene 2002, 21:5450-5461.
9. Plebani M., Basso D., Navaglia F., De Paoli M., Tommasini A., Cipriani A. Clinical evaluation of seven tomour markers in lung cancer diagnosis: can any combination improve the results?. Br. J. Cancer 1995, 72:170-173.
10. Bhattacharjee A., Richards W.G., Staunton J., Li C., Monti S., Vasa P., Lass C., Beheshti J., Bueno R., Gillette M., Loda M., Weber G., Mark E.J., Lander E.S., Wong W., Jonhson B.E., Golub T.R., Suqarbaker D.J., Meyerson M. Classification of human lung cancer carcinoma by mRNA expression profiling reveals distinct adenocarcinoma subclasses. PNAS 2001, 98:13790-13795.
11. Gordon G.J., Jensen R.V., Hsiao L.L., Gullans S.R., Blumenstock J.E., Ramaswamy S., Richards W.G., Sugarbaker D.J., Bueno R. Translation of microarray data into clinically relevant cancer dianostic test using gene expression ratios in lung cancer and mesothelioma. Cancer Res. 2002, 62:4963-4967.
12. Lee E., Chuang H.Y., Kim J.W., Ideker T., Lee D. Inferring pathway activity toward precise disease classification. PLoS Comput. Biol. 2008, 4(11):e1000217. 10.1371/journal.pcbi.1000217.
13. Sootanan P., Prom-on S., Meechai A., Chan J.H. Pathway-based microarray analysis for robust disease classification. Neural Comput. Appl. 2012, 21:649-660.
14. J.H. Chan, P. Sootanan, P. Larpeampaisarl, Feature selection of pathway markers for microarray-based disease classification using negatively correlated feature sets, in: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2011), IEEE Press, New York, 2011, pp.3293-3299.
15. Garcia-Pedrajas E., Ortiz-Boyer D. Improving multiclass pattern recognition by the combination of two strategies. Pattern Anal. Mach. Intell., IEEE Trans. 2006, 28(6):1001-1006.
16. Ramaswamy S., Tamayo P., Rifkin R., Mukherjee S., Yeang C.H., Angelo M., Ladd C., Reich M., Latulippe E., Mesirov J.P., Poggio T., Gerald W., Loda M., Lander E.S., Golub T.R. Multiclass cancer diagnosis using tumor gene expression signatures. PNAS 2001, 98:15149-15154.
17. Liu J.J., Cutler G., Li W., Pan Z., Peng S., Hoey T., Chen L., Ling X.B. Muticlass cancer classification and biomarker discovery using GA-based algorithms. Bioinformatics 2004, 21:2691-2697.
18. Subramanian A., Tamayo P., Mootha V.K., Mukherjee S., Ebert B.L., Gillete M.A., Paulovich A., Pomeroy S.L., Golub T.R., Lander E.S., Mesirov J.P. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. PNAS 2005, 102:15545-15550.
19. W. Engchuan, J.H. Chan, Pathway-based multi-class classification of lung cancer, in: Proceedings of the International Conference, ICONIP, LNCS 7667, 2012, pp. 697-702.
20. Hand D.J., Till R.J. A simple generalisation of the area under the ROC curve for multiple class classification problems. Mach. Learn. 2001, 45:171-186.
21. Hall M., Frank E., Holmes G., Pfahringer B., Reutemann R., Witten H.I. The WEKA data mining software: an update. ACM SIGKDD Explorations Newsletter 2009, 11(1):10-18.
22. Fleige S., Pfaffl M.W. RNA integrity and the effect on the real-time qRT-PCR performance. Mol. Asp. Med. 2006, 27:126-139.
23. Watskin W.S., Rogers A.R., Jorde L.B. Genetic variation among world populations: inferences from 100 Alu insertion polymorphisms. Genome Res. 2003, 13:1607-1618.
24. Kanehisa M., Goto S., Sata Y., Furumichi M., Tanabe M. KEGG for integration and interpretation of large-scale molecular database. Nucleic Acids Res. 2012, 40:D109-D114.
25. Kanehisa M., Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000, 28:27-30.