Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes

DOI10.1073/pnas.1732547100zbMath1130.62368OpenAlexW2120391288WikidataQ35917535 ScholiaQ35917535MaRDI QIDQ5460804

Ziv Bar-Joseph, David K. Gifford, Itamar Simon, Georg Gerber, Tommi S. Jaakkola

Publication date: 19 July 2005

Published in: Proceedings of the National Academy of Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1073/pnas.1732547100

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40)

Related Items (9)

Bayesian state space models for dynamic genetic network construction across multiple tissues ⋮ Modeling Persistent Trends in Distributions ⋮ A multivariate empirical Bayes statistic for replicated microarray time course data ⋮ Identifying temporally differentially expressed genes through functional principal components analysis ⋮ Bayesian models for two-sample time-course microarray experiments ⋮ A wavelet-based approach for imputation in nonstationary multivariate time series ⋮ Bayesian Hierarchical Modeling for Time Course Microarray Experiments ⋮ On Gene Ranking Using Replicated Microarray Time Course Data ⋮ Gene hunting with forests for multigroup time course data

Cites Work

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