A unified framework for finding differentially expressed genes from microarray experiments

BMC Bioinformatics

Volumn 8, Issue , 2007, Pages

  Shaik, Jahangheer S ^a   Yeasin, Mohammed ^a,b,c  

^a University of Memphis ^*  (United States)

^b University of Memphis   (United States)

^c UNIVERSITY OF MEMPHIS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIFFERENT DISTRIBUTIONS; DIFFERENTIALLY EXPRESSED GENE; FALSE DISCOVERY RATE; GENE SELECTION ALGORITHMS; MICROARRAY DATA SETS; MICROARRAY EXPERIMENTS; SIGNIFICANCE ANALYSIS; SIGNIFICANCE ANALYSIS OF MICROARRAYS;

CLUSTERING ALGORITHMS; DATA REDUCTION; DISEASES; EXPERIMENTS; MICROARRAYS; SCALABILITY; STATISTICAL TESTS; VISUALIZATION;

GENES;

ACCURACY; ARTICLE; BIOINFORMATICS; CANCER GENETICS; CLUSTER ANALYSIS; CONTROLLED STUDY; DATA BASE; DNA MICROARRAY; GENE EXPRESSION; GENE IDENTIFICATION; GENETIC ALGORITHM; INFORMATION PROCESSING; INTERMETHOD COMPARISON; LEUKEMIA; PARKINSON DISEASE; PERFORMANCE; SIMULATION; STATISTICAL SIGNIFICANCE; STOMACH CANCER; VALIDATION PROCESS; ALGORITHM; AUTOMATED PATTERN RECOGNITION; GENE EXPRESSION PROFILING; METHODOLOGY;

ALGORITHMS; CLUSTER ANALYSIS; GENE EXPRESSION PROFILING; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED;

EID: 36849048894     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-8-347     Document Type: Article

References (34)

1. Guyon I An Introduction of Variable and Feature Selection Journal of Machine Learning Research 2003, 3(7-8):1157-1182.
2. Getz G Levine E Domany E Coupled two-way clustering of gene microarray data Proceedings of National Academy of Science, USA 2000, 97(22):12079-12084.
3. Mukherjee S Roberts SJ Laan MJ Data-adaptive Test Statistics for Microarray Data Bioinformatics 2005, 21(2):108-114.
4. Shaik J Yeasin M Adaptive Ranking and Selection of Differentially Expressed Genes from Microarray Data WSEAS transactions on Biology and Biomedicine 2006, 3(2):125-133.
5. Hui-Huang H Advanced Data Mining Technologies in Bioinformatics Idea Group Publishing 2006, 329.
6. Tang C Zhang A Interrelated Two-way Clustering: An unsupervised approach for gene expression data analysis In Proceedings of the 2nd IEEE international Symposium on Bioinformatics and Bioengineering 2001, 14(4):41-48.
7. McLachlan GJ Bean RW Peel D A mixture model-based approach to the clustering of microarray expression data Bioinformatics 2002, 18(3):413-422. 11934740
8. Alon U Barkai N Notterman DA K.Gish 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. 21986 10359783
9. Tamayo P Slonim D Mesirov J Zhu Q Kitareewan S Dmitrovsky E Lander E Golub T Interpreting Patterns of Gene Expression with Self-Organizing Maps: Methods and Applications to Hematopoietic differentiation Proc Natl Acad Sci 1999, 96:2907-2912. 15868 10077610
10. Tavazoie S Hughes J Campbell M Cho R Church G Cluster Analysis and Display of Genome Wide Expression Patterns Nat Genetics 1999, 22:281-285.
11. Sahai H Ojeda MM Analysis of Variance for Random Models: Theory, Methods, Applications and Data Analysis Birkhauser 2004, 484.
12. Casella G Berger RL Statistical Inference Duxbury Advanced Series Duxbury Press 2 2001.
13. Tusher VG Tibshirani R Chu G Significance Analysis of Microarrays Applied to The Ionizing Radiation Response PNAS 2001, 98(9):5116-5121. 33173 11309499
14. Jeffery IB Higgins DG Culhane AC Comparison and Evaluation of Methods for Generating Differentially Expressed Gene lists from MicroArray Data BMC Bioinformatics 2006, 7:359-375. 1544358 16872483
15. Benjamini Y Hochberg Y Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing J R Statistical Society 1995, 57(1):289-300.
16. Benjamini Y Yekutieli D The Control of The False Discovery Rate in Multiple Testing Under Dependency The Annals of Statistics 2001, 29(4):1165-1188.
17. Storey JD Tibshirani R Statistical Significance for Genome Wide Studies PNAS 2003, 100(16):9440-9445. 170937 12883005
18. Fernando RL Nettleton D Southey BR Dekkers JCM Rothschild MF Soller M Controlling the Proportion of False Positives in Multiple Dependent Tests Genetics 2004, 166(1):611-619. 1470704 15020448
19. Shaik J Yeasin M Ranking Function Based on Higher Order Statistics (RF-HOS) for Two-Sample Microarray Experiments: May; Atlanta, GA. Springer Verlag Mandoiu I, Zelikovsky A 2007 LNBI 4463 97-108.
20. Zhang C Lu X Zhang X Significance of Gene Ranking for Classification of Microarray Samples IEEE/ACM Transactions on Computational Biology and Bioinformatics 2006, 3(3):312-320.
21. Shaik J Yeasin M A Progressive Framework for Two-Way Clustering Using Adaptive Subspace Iteration for Functionally Classifying Genes Proceedings of IEEE IJCNN'06, Vancouver, Canada 2006:5287-5292.
22. Shaik J Yeasin M Visualization of High Dimensional Data using an Automated 3D Star Co-ordinate System Proceedings of IEEE IJCNN'06, Vancouver, Canada 2006, 2318-2325.
23. Shaik J Yeasin M Functionally Classifying Genes from Microarray Data Using Linear and Non-linear Data Projection IEEE International Conference on Computer Systems and Applications 2006, 608-615.
24. Stekel D Microarray Bioinformatics Cambridge, Cambridge University Press 1 2003:263.
25. Davies DL Bouldin DW A Cluster Separation Measure IEEE Transactions on Pattern Analysis and Machine Intelligence 1979, 1:224-227.
26. Li T Ma S M.Ogihara Document Clustering via Adaptive Subspace Iteration Special Information Group on Information Retrieval 2004, 2004:218-225.
27. Lonnstedt I Speed T Replicated Microarray Data Statistica Sinica 2002, 12:31-46.
28. Purdom E Holmes S Error Distribution for Gene Expression Data Statistical Applications in Genetics and Molecular Biology California, Stanford University 2005, 4(1):1-5.
29. Chen X Leung SY Yeuen ST Chu KM Ji J Li R Chan ASY Law S Troyanskaya OG Wong J So S Botstein D Brown PO Variation in Gene Expression Patterns in Human Gastric Cancers Mol Bio Cell 2003, 14:3208-3215.
30. 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, 286:531-537. 10521349
31. Miller RM Callahan LM Casaceli C Chen L Kiser GL Chui B Kaysser-kranich TM Sendera TJ Palaniappan C Federoff HJ Dysregulation of Gene Expression in the 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine- Lesioned Mouse Substantia Nigra Journal of Neuroscience 2004, 24(34):7445-7454. 15329391
32. Duda RO E.Hart P G.Stork D Pattern Classification John Wiley and Sons Inc 2nd 2000.
33. Su Y Murali TM Pavlovic V Schaffer M Kasif S rankgene:IDentication of Diagnostic Genes Based on Expression Data 2002 http://genomics10buedu/ yangsu/rankgene/
34. Fisher RA The use of multiple measurements in taxonomic problems Annual Eugenics 1936, 7(2):179-188.