TSG: A new algorithm for binary and multi-class cancer classification and informative genes selection

BMC Medical Genomics

Volumn 6, Issue SUPPL.1, 2013, Pages

  Wang, Haiyan ^a   Zhang, Hongyan ^b,c   Dai, Zhijun ^b,c   Chen, Ming Shun ^a   Yuan, Zheming ^b,c  

^a KANSAS STATE UNIVERSITY   (United States)

^b Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization   (China)

^c HUNAN AGRICULTURAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; CANCER CLASSIFICATION; CLASSIFICATION ALGORITHM; COMPUTER ANALYSIS; COMPUTER PREDICTION; COMPUTER PROGRAM; CONTROLLED STUDY; DATA ANALYSIS; GENE EXPRESSION; GENETIC ALGORITHM; GENETIC MARKER; GENETIC SELECTION; INTERMETHOD COMPARISON; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; TOP SCORING GENES CLASSIFIER; VALIDATION PROCESS;

ALGORITHMS; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; TUMOR MARKERS, BIOLOGICAL;

EID: 84872920672     PISSN: None     EISSN: 17558794     Source Type: Journal    
DOI: 10.1186/1755-8794-6-S1-S3     Document Type: Article

References (33)

1. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Tibshirani R, Hastie T, Narasimhan B, Chu G, Proc Natl Acad Sci USA 2002 99 6567 6572 10.1073/pnas.082099299 12011421 (Pubitemid 34526173)
2. Classifying Gene Expression Profiles from Pairwise mRNA Comparisons. Geman D, d'Avignon C, Naiman D, Winslow R, Statistical Applications in Genetics and Molecular Biology 2004 doi: 10.2202/1544-6115.1071
3. Simple decision rules for classifying human cancers from gene expression profiles. Tan AC, Naiman DQ, Xu L, Winslow RL, Geman D, Bioinformatics 2005 21 3896 3904 10.1093/bioinformatics/bti631 16105897 (Pubitemid 41535505)
4. LIBSVM: a library for support vector machines. Chang CC, Lin CJ, ACM Transactions on Intelligent, Systems and Technology 2011 2 27 1 27
5. A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression. Li T, Zhang C, Ogihara M, Bioinformatics 2004 20 2429 2437 10.1093/bioinformatics/bth267 15087314 (Pubitemid 39429915)
6. A stable gene selection in microarray data analysis. Yang K, Cai Z, Li J, Lin G, BMC Bioinformatics 2006 7 228 10.1186/1471-2105-7-228 16643657 (Pubitemid 44164726)
7. Minimum redundancy feature selection from microarray gene expression data. Ding C, Peng H, J Bioinform Comput Biol 2005 3 2 185 205 10.1142/S0219720005001004 15852500 (Pubitemid 40561382)
8. Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data. Ooi CH, Chetty M, Teng SW, BMC Bioinformatics 2006 7 320 10.1186/1471-2105-7-320 16796748 (Pubitemid 44399877)
9. Gene selection for classification of microarray data based on the bayes error. Zhang JG, Deng HW, BMC Bioinformatics 2007 8 1 37 10.1186/1471-2105-8-37 17270045 (Pubitemid 46322149)
10. Exploring the within and between class correlation distributions for tumor classification. Wei X, Li K, Proc Natl Acad Sci USA 2010 107 15 6737 6742 10.1073/pnas.0910140107 20339085
11. Gene selection and classification for cancer microarray data based on machine learning and similarity measures. Liu Q, Sung A, Chen Z, Chen L, Liu J, Qiao M, Wang Z, Huang X, Deng Y, BMC Genomics 2011 12 Suppl 5 1 doi:10.1186/1471-2164-12-S5-S1 10.1186/1471-2164-12-S5-S1 22369514
12. Gene selection for cancer classification using support vector machines. Guyon I, Weston J, Barnhill S, Vapnik V, Machine learning 2002 46 389 422 10.1023/A:1012487302797 (Pubitemid 34129977)
13. Variable selection using svm based criteria. Rakotomamonjy A, J Mach Learn Res 2003 3 1357 1370
14. Gene selection and classification of microarray data using random forest. Daz-Uriarte R, Alvarez de Andrés S, BMC Bioinformatics 2006 7 3 doi:10.1186/1471-2105-7-3 10.1186/1471-2105-7-3 16398926 (Pubitemid 43085344)
15. The random subspace method for constructing decision forests. Ho TK, IEEE Transactions on Pattern Analysis and Machine Intelligence 1998 20 8 832 844 10.1109/34.709601 (Pubitemid 128741345)
16. Weighted random subspace method for high dimensional data classification. Li X, Zhao H, Statistics and its Interface 2009 2 153 159 21918713
17. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. 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, Nature 2000 403 503 511 10.1038/35000501 10676951 (Pubitemid 30082188)
18. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Alon U, Barkai N, Notterman DA, Gish K, Ybarra S, Mack D, Levine AJ, Proc Natl Acad Sci USA 1999 96 6745 6750 10.1073/pnas.96.12.6745 10359783 (Pubitemid 29274954)
19. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES, Science 1999 286 5439 531 537 10.1126/science.286.5439.531 10521349
20. Prediction of central nervous system embryonal tumour outcome based on gene expression. 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, Nature 2002 415 436 442 10.1038/415436a 11807556 (Pubitemid 34100955)
21. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. 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, Nat Med 2002 8 68 74 10.1038/nm0102-68 11786909 (Pubitemid 34101731)
22. Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma. Gordon GJ, Jensen RV, Hsiao LL, Gullans SR, Blumenstock JE, Ramaswami S, Richards WG, Sugarbaker DJ, Bueno R, Cancer Res 2002 62 4963 4967 12208747 (Pubitemid 34984420)
23. Gene expression correlates of clinical prostate cancer behaviour. 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, Cancer Cell 2002 1 203 209 10.1016/S1535-6108(02)00030-2 12086878 (Pubitemid 41039166)
24. In silico dissection of cell-type-associated patterns of gene expression in prostate cancer. Stuart RO, Wachsman W, Berry CC, Wang-Rodriguez J, Wasserman L, Klacansky I, Masys D, Arden K, Goodison S, McClelland M, Wang Y, Sawyers A, Kalcheva I, Tarin D, Mercola D, Proc Natl Acad Sci USA 2004 101 615 620 10.1073/pnas.2536479100 14722351 (Pubitemid 38084685)
25. Analysis of Gene Expression Identifies Candidate Markers and Pharmacological Targets in Prostate Cancer. Welsh JB, Sapinoso LM, Su AI, Kern SG, Wang-Rodriguez J, Moskaluk CA, Frierson HF Jr, Hampton GM, Cancer Res 2001 61 5974 5978 11507037 (Pubitemid 32762523)
26. Multiclass cancer diagnosis using tumor gene expression signatures. Ramaswamy S, Tamayo P, Rifkin R, Mukherjee S, Yeang CH, Angelo M, Ladd C, Reich M, Latulippe E, Mesirov JP, Poggio T, Gerald W, Loda M, Lander ES, Golub TR, Proc Natl Acad Sci USA 2001 98 15149 15154 10.1073/pnas.211566398 11742071 (Pubitemid 34013984)
27. Gene-expression profiles predict survival of patients with lung adenocarcinoma. Beer DG, Kardia SL, Huang CC, Giordano TJ, Levin AM, Misek DE, Lin L, Chen G, Gharib TG, Thomas DG, Lizyness ML, Kuick R, Hayasaka S, Taylor JM, Iannettoni MD, Orringer MB, Hanash S, Nat Med 2002 8 816 824 12118244
28. MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Armstrong SA, Staunton JE, Silverman LB, Pieters R, den Boer ML, Minden MD, Sallan SE, Lander ES, Golub TR, Korsmeyer SJ, Nat Genet 2002 30 41 47 10.1038/ng765 11731795
29. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Khan J, Wei JS, Ringnér M, Saal LH, Ladanyi M, Westermann F, Berthold F, Schwab M, Antonescu CR, Peterson C, Meltzer PS, Nat Med 2001 7 673 679 10.1038/89044 11385503 (Pubitemid 32588022)
30. Molecular portraits of human breast tumours. Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lønning PE, Børresen-Dale AL, Brown PO, Botstein D, Nature 2000 406 747 752 10.1038/35021093 10963602
31. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Bhattacharjee A, Richards WG, Staunton J, Li C, Monti S, Vasa P, Ladd C, Beheshti J, Bueno R, Gillette M, Loda M, Weber G, Mark EJ, Lander ES, Wong W, Johnson BE, Golub TR, Sugarbaker DJ, Meyerson M, Proc Natl Acad Sci USA 2001 98 13790 13795 10.1073/pnas.191502998 11707567 (Pubitemid 33115977)
32. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. 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, Cancer Cell 2002 1 133 143 10.1016/S1535-6108(02) 00032-6 12086872 (Pubitemid 41039160)
33. Molecular classification of human carcinomas by use of gene expression signatures. Su AI, Welsh JB, Sapinoso LM, Kern SG, Dimitrov P, Lapp H, Schultz PG, Powell SM, Moskaluk CA, Frierson HF Jr, Hampton GM, Cancer Res 2001 61 7388 7393 11606367 (Pubitemid 32995021)