scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/jcb/StegleDCWGB10 |
P356 | DOI | 10.1089/CMB.2009.0175 |
P932 | PMC publication ID | 3198888 |
P698 | PubMed publication ID | 20377450 |
P5875 | ResearchGate publication ID | 43078878 |
P50 | author | Zoubin Ghahramani | Q8074621 |
Katherine J Denby | Q38317622 | ||
Oliver Stegle | Q41049272 | ||
Karsten Borgwardt | Q47461780 | ||
P2093 | author name string | David L Wild | |
Emma J Cooke | |||
P2860 | cites work | Significance analysis of time course microarray experiments | Q28769495 |
BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks | Q29547427 | ||
Analysis of variance for gene expression microarray data | Q29618940 | ||
Gaussian process robust regression for noisy heart rate data | Q31172572 | ||
BATS: a Bayesian user-friendly software for analyzing time series microarray experiments | Q33374141 | ||
Gaussian process regression bootstrapping: exploring the effects of uncertainty in time course data | Q33418535 | ||
The Arabidopsis Information Resource (TAIR): gene structure and function annotation. | Q34008043 | ||
Bayesian coclustering of Anopheles gene expression time series: study of immune defense response to multiple experimental challenges. | Q34144499 | ||
Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes | Q35917535 | ||
Crosstalk between abiotic and biotic stress responses: a current view from the points of convergence in the stress signaling networks | Q36499476 | ||
A Bayesian approach to estimation and testing in time-course microarray experiments | Q40073388 | ||
Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities | Q45795868 | ||
maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments | Q48457269 | ||
Benchmarking the CATMA microarray. A novel tool for Arabidopsis transcriptome analysis | Q51540622 | ||
P433 | issue | 3 | |
P304 | page(s) | 355-367 | |
P577 | publication date | 2010-03-01 | |
P1433 | published in | Journal of Computational Biology | Q6295003 |
P1476 | title | A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series | |
P478 | volume | 17 |
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