Transcriptional Regulatory Networks in Saccharomyces cerevisiae

By Tong Ihn Lee, Nicola J. Rinaldi, F. Robert, Duncan T. Odom, Ziv Bar-Joseph, G. Gerber, N. Hannett, Christopher T. Harbison, C. M. Thompson, Itamar Simon and 11 more. Science, 2002

439 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/674b70b8f5c1115ed6c79b1325fc2cbb09ab019c

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Citations in the corpus

Gene regulatory network inference: Data integration in dynamic models - A review (2009, background): “This facilitates the decomposition of biological networks into basic recurring modular components that consist of only a few genes, so-called network motifs (Shen-Orr et al., 2002; Lee et al., 2002).”
Group SCAD regression analysis for microarray time course gene expression data (2007, positive): “We applied the mixture model approach described in previous section using the ChIP data of Lee et al. (2002) to derive the binding probabilities Xik for these 297 cell cycle regulated genes for a total of 96 TFs with at least one non-zero binding probability in the 297 genes.”
A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches. (2009, neutral): “These interactions coexist normally in many transcriptional pathways in higher eukaryotes (Lee et al., 2002).”
Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities (2006, methodology): “Although recent techniques such as Chromatine Immunoprecipitation (ChIP) (Lee et al., 2002; Harbison et al., 2004) have uncovered much information about the architecture, or connectivity, of the networks, any quantitative model would require the knowledge of both the concentration of transcription…”
Sparse partial least squares regression for simultaneous dimension reduction and variable selection (2010, background): “…which measures m rna levels at every 7 minutes for 119 minutes with a total of 18 measurements covering two cell cycle periods. c h ip -chip data of Lee et al. (2002) contains the binding information of 106 tf s which elucidate how yeast transcriptional regulators bind to promoter sequences of…”
Inference of gene regulatory networks and compound mode of action from time course gene expression profiles (2006, methodology): “Different experimental and computational methods have been proposed to tackle the network identification problem (Tong et al., 2002; Lee et al., 2002; Ideker et al., 2001; Davidson et al., 2002; Arkin et al., 1997; Yeung et al., 2002).”
Robustness of Cellular Functions (2004, neutral): “feedback control (Shen-Orr et al., 2002; Milo et al., 2002; Lee et al., 2002; Yeger-Lotem uncontrolled tumor growth (Kitano, 2004) .”
GENEVESTIGATOR. Arabidopsis Microarray Database and Analysis Toolbox1[w] (2004, background): “…exploitation of large-scale gene expression data-sets, mainly from Saccharomyces cerevisiae and Escherichia coli , has already led to the discovery of global structures governing metabolic and regulatory networks (Lee et al., 2002; Ravasz et al., 2002; Stelling et al., 2002; Ihmels et al., 2004).”
Computational prediction of transcription-factor binding site locations (2003, methodology): “This approach has been used to characterize a number of TFs in the yeast Saccharomyces cerevisiae [9,11-15] and,”