A new approach to analyzing gene expression time series data
- 18 April 2002
- conference paper
- conference paper
- Published by Association for Computing Machinery (ACM)
Abstract
No abstract availableThis publication has 14 references indexed in Scilit:
- Serial Regulation of Transcriptional Regulators in the Yeast Cell CycleCell, 2001
- Missing value estimation methods for DNA microarraysBioinformatics, 2001
- Statistical modeling of large microarray data sets to identify stimulus-response profilesProceedings of the National Academy of Sciences of the United States of America, 2001
- Dynamic modeling of gene expression dataProceedings of the National Academy of Sciences of the United States of America, 2001
- Fundamental patterns underlying gene expression profiles: Simplicity from complexityProceedings of the National Academy of Sciences of the United States of America, 2000
- Using Bayesian networks to analyze expression dataPublished by Association for Computing Machinery (ACM) ,2000
- Comprehensive Identification of Cell Cycle–regulated Genes of the YeastSaccharomyces cerevisiaeby Microarray HybridizationMolecular Biology of the Cell, 1998
- The Transcriptional Program of Sporulation in Budding YeastScience, 1998
- Smoothing Spline Models for the Analysis of Nested and Crossed Samples of CurvesJournal of the American Statistical Association, 1998
- Speech recognition using hidden Markov models with polynomial regression functions as nonstationary statesIEEE Transactions on Speech and Audio Processing, 1994