Park T, Yi S-G, Lee S, et al.: Statistical tests for identifying differentially expressed genes in time-course microarray experiments. Bioinformatics 2003, 19(6):694-703. 10.1093/bioinformatics/btg068
Article
Google Scholar
Peddada SD, Lobenhofer EK, Li L, Afshari CA, Weinberg CR, Umbach DM: Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference. Bioinformatics 2003, 19(7):834-841. 10.1093/bioinformatics/btg093
Article
Google Scholar
Storey JD, Xiao W, Leek JT, Tompkins RG, Davis RW: Significance analysis of time course microarray experiments. Proceedings of the National Academy of Sciences of the United States of America 2005, 102(36):12837-12842. 10.1073/pnas.0504609102
Article
Google Scholar
Tai YC, Speed TP: A multivariate empirical Bayes statistic for replicated microarray time course data. The Annals of Statistics 2006, 34(5):2387-2412. 10.1214/009053606000000759
Article
MathSciNet
MATH
Google Scholar
Ramoni MF, Sebastiani P, Kohane IS: Cluster analysis of gene expression dynamics. Proceedings of the National Academy of Sciences of the United States of America 2002, 99(14):9121-9126. 10.1073/pnas.132656399
Article
MathSciNet
MATH
Google Scholar
Ernst J, Nau GJ, Bar-Joseph Z: Clustering short time series gene expression data. Bioinformatics 2005, 21(1):i159-i168. 10.1093/bioinformatics/bti1022
Article
Google Scholar
Giurcǎneanu CD, Tǎbuş I, Astola J: Clustering time series gene expression data based on sum-of-exponentials fitting. EURASIP Journal on Applied Signal Processing 2005, 2005(8):1159-1173. 10.1155/ASP.2005.1159
Article
Google Scholar
Heard NA, Holmes CC, Stephens DA, Hand DJ, Dimopoulos G: Bayesian coclustering of Anopheles gene expression time series: study of immune defense response to multiple experimental challenges. Proceedings of the National Academy of Sciences of the United States of America 2005, 102(47):16939-16944. 10.1073/pnas.0408393102
Article
Google Scholar
Conesa A, Nueda MJ, Ferrer A, Talón M: maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics 2006, 22(9):1096-1102. 10.1093/bioinformatics/btl056
Article
Google Scholar
Letowski J, Brousseau R, Masson L: Designing better probes: effect of probe size, mismatch position and number on hybridization in DNA oligonucleotide microarrays. Journal of Microbiological Methods 2004, 57(2):269-278. 10.1016/j.mimet.2004.02.002
Article
Google Scholar
Ramsay J, Silverman B: Functional Data Analysis. 2nd edition. Springer, New York, NY, USA; 2005.
Google Scholar
Bar-Joseph Z, Gerber GK, Gifford DK, Jaakkola TS, Simon I: Continuous representations of time-series gene expression data. Journal of Computational Biology 2003, 10(3-4):341-356. 10.1089/10665270360688057
Article
Google Scholar
Bar-Joseph Z: Analyzing time series gene expression data. Bioinformatics 2004, 20(16):2493-2503. 10.1093/bioinformatics/bth283
Article
Google Scholar
Martin PGP, Lasserre F, Calleja C, et al.:Transcriptional modulations by RXR agonists are only partially subordinated to PPAR
signaling and attest additional, organ-specific, molecular cross-talks. Gene Expression 2005, 12(3):177-192. 10.3727/000000005783992098
Article
Google Scholar
Martin PGP, Guillou H, Lasserre F, et al.:Novel aspects of PPAR
-mediated regulation of lipid and xenobiotic metabolism revealed through a nutrigenomic study. Hepatology 2007, 45(3):767-777. 10.1002/hep.21510
Article
Google Scholar
INRArray: Laboratoire de Pharmacologie et Toxicologie, INRA.2005. [http://www.inra.fr/internet/Centres/toulouse/pharmacologie/lpt.htm]
Google Scholar
Silverman B: Some aspects of the spline smoothing approach to non-parametric regression curve fitting. Journal of the Royal Statistical Society: Series B 1985, 47(1):1-52.
MathSciNet
MATH
Google Scholar
Besse P, Cardot H, Ferraty F: Simultaneous non-parametric regressions of unbalanced longitudinal data. Computational Statistics & Data Analysis 1997, 24(3):255-270. 10.1016/S0167-9473(96)00067-9
Article
MathSciNet
MATH
Google Scholar
Seber GAF: Multivariate Observations. John Wiley & Sons, New York, NY, USA; 1984.
Book
MATH
Google Scholar
Yeung KY, Ruzzo WL: Principal component analysis for clustering gene expression data. Bioinformatics 2001, 17(9):763-774. 10.1093/bioinformatics/17.9.763
Article
Google Scholar
Chipman H, Hastie TJ, Tibshirani T: Clustering microarray data. In Statistical Analysis of Gene Expression Microarray Data. Edited by: Speed T. Chapmann & Hall/CRC Press, Boca Raton, Fla, USA; 2003:159-200.
Google Scholar
Kersten S, Seydoux J, Peters JM, Gonzalez FJ, Desvergne B, Wahli W:Peroxisome proliferator-activated receptor
mediates the adaptive response to fasting. Journal of Clinical Investigation 1999, 103(11):1489-1498. 10.1172/JCI6223
Article
Google Scholar
Mandard S, Müller M, Kersten S:Peroxisome proliferator-activated receptor
target genes. Cellular and Molecular Life Sciences 2004, 61(4):393-416. 10.1007/s00018-003-3216-3
Article
Google Scholar
Bauer M, Hamm AC, Bonaus M, et al.: Starvation response in mouse liver shows strong correlation with life-span-prolonging processes. Physiological Genomics 2004, 17(2):230-244. 10.1152/physiolgenomics.00203.2003
Article
Google Scholar