A joint finite mixture model for clustering genes from independent Gaussian and beta distributed data

BMC Bioinformatics

Volumn 10, Issue , 2009, Pages

  Dai, Xiaofeng ^a   Erkkilä, Timo ^a   Yli Harja, Olli ^a   Lähdesmäki, Harri ^a  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

AKAIKE INFORMATION CRITERION; BAYESIAN INFORMATION CRITERION; DISTRIBUTED RANDOM VARIABLES; EXPECTATION-MAXIMIZATION ALGORITHMS; HETEROGENEOUS INFORMATION SOURCES; INTEGRATED CLASSIFICATION; MODEL SELECTION CRITERIA; PARAMETRIC DISTRIBUTIONS;

ALGORITHMS; CLUSTER ANALYSIS; GAUSSIAN DISTRIBUTION; GENE EXPRESSION; IMAGE SEGMENTATION; SIGNAL TRANSDUCTION; STATISTICAL TESTS;

COMPUTER SIMULATION;

DNA; MYELOID DIFFERENTIATION FACTOR 88; TOLL LIKE RECEPTOR 3; TOLL LIKE RECEPTOR 4;

ARTICLE; BAYES THEOREM; CLUSTER ANALYSIS; GENE CLUSTER; GENE EXPRESSION; GENE FUNCTION; GENETIC ALGORITHM; KERNEL METHOD; NONHUMAN; PARAMETRIC TEST; PROBABILITY; PROTEIN DNA BINDING; SIGNAL TRANSDUCTION; STATISTICAL DISTRIBUTION; STATISTICAL MODEL; ALGORITHM; ANIMAL; GENE EXPRESSION PROFILING; METHODOLOGY; MOUSE; NORMAL DISTRIBUTION;

ALGORITHMS; ANIMALS; CLUSTER ANALYSIS; GENE EXPRESSION PROFILING; MICE; NORMAL DISTRIBUTION;

EID: 68149180905     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-165     Document Type: Article

References (20)

1. Jiang DX Tang C D ZA Cluster analysis for gene expression data: A survey IEEE Transactions on Knowledge and Data Engineering 2004, 16(11):1370-1386. 10.1109/TKDE.2004.68
2. Lähdesmäki H Rust AG Shmulevich I Probabilistic Inference of Transcription Factor Binding from Multiple Data Sources PLoS ONE 2008, 3(3):e1820. 2268002 18364997 10.1371/journal.pone.0001820
3. Ji Y Wu C Liu P Wang J Coombes RK Applications of beta-mixture models in bioinformatics Bioinformatics 2005, 21(9):2118-2122. 10.1093/ bioinformatics/bti318 15713737
4. Durbin R Eddy SR Krogh A Mitchison G Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids Cambridge: Cambridge University Press 1999.
5. Fraley C Raftery AE Model-based clustering, discriminant analysis, and density estimation Journal of the American Statistical Association 2002, 97:611-631. 10.1198/016214502760047131
6. Smyth P Model selection for probabilistic clustering using cross-validated likelihood Statistics and Computing 2000, 9:63-72. 10.1023/A:1008940618127
7. Biernacki C Govaert G Choosing models in model-based clustering and discriminant analysis Journal of Statistical Computarion and Simularion 1999, 64:49-71. 10.1080/00949659908811966
8. Mclachlan G Peel D Finite mixture models New York: John Wiley & Sons 2000.
9. Lee TI Rinaldi NJ Robert F Odom DT Bar-Joseph Z Gerber GK Hannett NM Harbison CT Thompson CM Simon I Zeitlinger J Jennings EG Murray HL Gordon DB Ren B Wyrick JJ Tagne JB Volk-ert TL Fraenkel E Gifford DK Young RA Transcriptional regulatory networks in Saccharomyces cerevisiae Science 2002, 298(5594):799-804. 10.1126/science.1075090 12399584
10. Pan W Incorporating gene functions as priors in model-based clustering of microarray gene expression data Bioinformatics 2006, 22(7):795-801. 10.1093/bioinformatics/btl011 16434443
11. Schwarz G Estimating the dimension of a model The Annals of Statistics 1978, 6(2):461-464. 10.1214/aos/1176344136
12. Akaike H A new look at the statistical identification model IEEE Transactions on Automatic Control 1974, 19:716-723. 10.1109/ TAC.1974.1100705
13. Bozdogan H Model Selection and Akaike Information Criterion (AIC): The General Theory and its Analytic Extensions Psychometrika 1987, 52(3):345-370. 10.1007/BF02294361
14. Ramsey SA Klemm SL Zak DE Kennedy KA Thorsson V Li B Gilchrist M Gold ES Johnson CD Litvak V Navarro G Roach JC Rosenberger CM Rust AG Yudkovsky N Aderem A Shmulevich I Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics PLoS Computational Biology 2008, 4(2):e1000021. 2265556 18369420 10.1371/ journal.pcbi.1000021
15. Jr GD Sherman BT Hosack DA Yang J Gao W Lane HC A LR DAVID: Database for Annotation, Visualization, and Integrated Discovery Genome Biology 2003, 4(9):R60. 10.1186/gb-2003-4-9-r60
16. Oyake T Itoh K Motohashi H Hayashi N Hoshino H Nishizawa M Yamamoto M Igarashi K Bach Proteins Belong to a Novel Family of BTB-Basic Leucine Zipper Transcription Factors That Interact with MafK and Regulate Transcription through the NF-E2 Site Molecular and Cellular Biology 1996, 16(11):6083-6095.
17. Kobayashi A Yamagiwa H Hoshino H Muto A Sato K Morita M Hayashi N Yamamoto M Igarashi K A Combinatorial Code for Gene Expression Generated by Transcripton Factor Bach2 and MAZR (MAZ-Related Factor) through the BTB/POZ Domain Molecular and Cellular Biology 2000, 20(5):1733-1746. 10.1128/MCB.20.5.1733-1746.2000
18. Okada Y Expression of AP-1 (c-fos/c-jun) in developing mouse corneal epithelium Graefe's Archive for Clinical and Experimental Ophthalmology 2003, 241(4):330-333. 10.1007/s00417-003-0625-9
19. O'Neill LA Fitzgerald KA Bowie AG The Toll-IL-1 receptor adaptor family grows to five members Trends in Immunology 2003, 24(6):286-290. 10.1016/ S1471-4906(03)00115-7 12810098
20. Bjökbacka H Fitzgerald KA Huet F Li XM Gregory JA Lee MA Ordija CM Dowley NE Golenbock DT Freeman MW The induction of macrophage gene expression by LPS predominantly utilizes Myd88-independent signaling cascades Physiological Genomics 2005, 19:319-330. 10.1152/ physiolgenomics.00128.2004