Multivariate curve resolution of time course microarray data

BMC Bioinformatics

Volumn 7, Issue , 2006, Pages

  Wentzell, Peter D ^a   Karakach, Tobias K ^a   Roy, Sushmita ^b   Juanita, M Juanita ^b   Allen, Christopher P ^b   Werner Washburne, Margaret ^b  

^a DALHOUSIE UNIVERSITY   (Canada)

^b UNIVERSITY OF NEW MEXICO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL INTERPRETATION; INDEPENDENT COMPONENT ANALYSIS(ICA); LINEAR-DECOMPOSITION; MISSING MEASUREMENTS; MULTIVARIATE CURVE RESOLUTION; NON-NEGATIVITY CONSTRAINTS; TIME-COURSE EXPERIMENTS; WEIGHTED LEAST SQUARES APPROACH;

ALGORITHMS; GENE EXPRESSION; INDEPENDENT COMPONENT ANALYSIS; LEAST SQUARES APPROXIMATIONS; MEASUREMENT ERRORS; PRINCIPAL COMPONENT ANALYSIS;

DATA MINING;

MESSENGER RNA; FUNGAL PROTEIN;

ARTICLE; BIOINFORMATICS; CELL CYCLE REGULATION; FUNGAL GENETICS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETIC ALGORITHM; INFORMATION RETRIEVAL; MATHEMATICAL ANALYSIS; MEASUREMENT ERROR; METHODOLOGY; MICROARRAY ANALYSIS; MULTIVARIATE ANALYSIS; MULTIVARIATE CURVE RESOLUTION WEIGHTED ALTERNATING LEAST SQUARE; NONHUMAN; SACCHAROMYCES CEREVISIAE; SCORING SYSTEM; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; CELL CYCLE; CHEMISTRY; DNA MICROARRAY; METABOLISM; PRINCIPAL COMPONENT ANALYSIS; PROCEDURES; STATISTICAL ANALYSIS; TIME FACTOR;

ALGORITHMS; CELL CYCLE; COMPUTATIONAL BIOLOGY; DATA INTERPRETATION, STATISTICAL; FUNGAL PROTEINS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MODELS, BIOLOGICAL; MULTIVARIATE ANALYSIS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; SACCHAROMYCES CEREVISIAE; TIME FACTORS;

EID: 33847098713     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-7-343     Document Type: Article

References (39)

1. Bar-Joseph Z Analyzing time series gene expression data Bioinformatics 2001 20 2493-2503 10.1093/bioinformatics/bth283
2. Lu P Nakorchevskiy A Marcotte EM Expression deconvolution: A reinterpretation of DNA microarray data reveals dynamic changes in cell populations Proc Natl Acad Sci USA 2003 100 10370-10375 193568-12934019 10.1073/pnas.1832361100
3. Holter NS Mitra M Maritan A Cieplak M Banavar JR Fereroff N Fundamental patterns underlying gene expression profiles: Simplicity from complexity Proc Natl Acad Sci USA 2000 97 8409-8414 26961 10890920 10.1073/ pnas.150242097
4. Raychaudhuri S Stuart JM Altman B Principal component analysis to summarize microarray experiments: Application to sporulation time series Pac Symp Biocomput 2000 5 452-463
5. 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 27718 10963673 10.1073/pnas.97.18.10101
6. Liu L Hawkins DM Ghosh S Young SS Robust singular value decomposition analysis of microarray data Proc Natl Acad Sci USA 2003 100 13167-13172 263735 14581611 10.1073/pnas.1733249100
7. Alter O Brown PO Botstein D Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms Proc Natl Acad Sci USA 2003 100 3351-3356 152296 12631705 10.1073/pnas.0530258100
8. Alter O Golub GH Integrative analysis of genome scale data by using pseudoinverse projection predicts novel correlation between DNA replication and RNA transcription Proc Natl Acad Sci USA 2004 101 16577-16582 534520 15545604 10.1073/pnas.0406767101
9. Liebermeister W Linear modes of gene expression determined by independent component analysis Bioinformatics 2002 18 51-60 10.1093/ bioinformatics/18.1.51 11836211
10. Lee SI Batzoglou S Application of independent component analysis to microarrays Genome Biol 2003 4 R76 329130 14611662 10.1186/ gb-2003-4-11-r76
11. Kreil DP MacKay DJC Reproducibility assessment of independent component analysis of expression ratios from DNA microarrays Comp Funct Genom 2003 4 300-317 10.1002/cfg.298
12. Segal E Battle A Koller D Decomposing gene expression into cellular processes Pac Symp Biocomput 2003 8 89-100
13. Bergmann S Ihmels J Barkai N Iterative signature algorithm for the analysis of large-scale gene expression data Phys Rev E 2003 67 031902/ 1-031902/18 10.1103/PhysRevE.67.031902
14. de Juan A Tauler R Chemometrics applied to unravel multicomponent processes and mixtures. Revisiting latest trends in multivariate resolution Anal Chim Acta 2003 500 195-210 10.1016/S0003-2670(03)00724-4
15. Jiang JH Liang Y Ozaki Y Principles and methodologies in self-modeling curve resolution Chemom Intell Lab Syst 2004 71 1-12 10.1016/ j.chemolab.2003.07.002
16. Rocke DM Durbin B A model for measurement error for gene expression arrays J Comput Biol 2001 8 557-569 10.1089/106652701753307485 11747612
17. Wentzell PD Andrews DT Hamilton DC Faber K Kowalski BR Maximum likelihood principal components analysis J Chemom 1997 11 339-366 10.1002/(SICI)1099-128X(199707)11:4<339::AID-CEM476>3.0.CO;2-L
18. Van Huffel S Vandewalle J The Total Least Squares Problem: Computational Aspects and Analysis Philadelphia: SIAM 1991
19. Lawton WH Sylvestre EA Self-modeling curve resolution Technometrics 1971 13 617-633 10.2307/1267173
20. Tauler R Kowalski B Fleming S Multivariate curve resolution applied to spectral data from multiple runs of an industrial process Anal Chem 1993 65 2040-2047 10.1021/ac00063a019
21. Malinowski ER Factor Analysis in Chemistry New York: Wiley 3rd edition 2002
22. Windig W Guilment J Interactive self-modeling mixture analysis Anal Chem 1991 63 1425-1432 10.1021/ac00014a016
23. de Juan A van den Bogaert B Cuesta Sanchez F Massart DL Application of the needle algorithm for exploratory analysis and resolution of HPLC-DAD data Chemom Intell Lab Syst 1996 33 133-145 10.1016/0169-7439(96)00009-3
24. Van Benthem M Keenan MR Fast algorithm for the solution of large-scale non-negativity-constrained least squares problems J Chemom 2004 18 441-450 10.1002/cem.889
25. Chen Y Dougherty ER Bittner ML Ratio-based decisions on the quantitative analysis of cDNA microarray images J Biomed Opt 1997 2 364-374 10.1117/ 12.281504
26. Ideker T Thorsson V Siegel AF Hood LE Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data J Comput Biol 2000 6 805-817 10.1089/10665270050514945
27. Yang MCK Ruan QG Yang JJ Eckenrode S Wu S McIndoe RA She JX A statistical method for flagging weak spots improves normalization and ratio estimates in microarrays Physiol Genomics 2001 7 45-53 11595791
28. Huber W von Heydebreck A Sültmann H Poustka A Vingron M Variance stabilization applied to microarray data calibration and to quantification of diferential expression Bioinformatics 2002 18 S96-S104 12169536
29. Cui X Kerr MK Churchill GA Transformations for cDNA microarray data Stat Appl Genet Mol Biol 2003 2 Article 4
30. Kim H Golub GH Park H Missing value estimation for DNA microarray gene expression data: Local least squares imputation Bioinformatics 2005 21 187-198 10.1093/bioinformatics/bth499 15333461
31. Schuemans M Markovsky I Wentzell PD Van Huffel S On the equivalence between total least squares and maximum likelihood PCA Anal Chim Acta 2005 544 254-267 10.1016/j.aca.2004.12.059
32. Spellman PT Sherlock G Zhang MQ Iyer VR Anders K Eisen B 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 25624 9843569
33. Borgen OS Kowalski BR An extension of the multivariate component-resolution method to three components Anal Chim Acta 1985 174 1-26 10.1016/S0003-2670(00)84361-5
34. Kim BM Henry RC Extension of self-modeling curve resolution to mixtures of more than three components Part 2. Finding the complete solution Chemom Intell Lab Syst 1999 49 67-77 10.1016/S0169-7439(99)00029-5
35. Rajkó R István K Analytical solution for determining feasible regions of self-modeling curve resolution (SMCR) method based on computational geometry J Chemomet 2005 19 448-463 10.1002/cem.947
36. Leger MN Wentzell PD Dynamic Monte Carlo self-modeling curve resolution method for multicomponent mixtures Chemom Intell Lab Syst 2002 62 171-188 10.1016/S0169-7439(02)00016-3
37. Gemperline PJ Computation of the range of feasible solutions in self-modeling curve resolution algorithms Anal Chem 1999 71 5398-5404 10.1021/ac990648y
38. Tauler R Calculation of maximum and minimum band boundaries of feasible solutions for species profilesobtained by multivariate curve resolution J Chemomet 2001 15 627-646 10.1002/cem.654
39. Dalhousie University Chemometrics Group Website http://myweb.dal.ca/ pdwentze/publications.html