Functional discovery via a compendium of expression profiles.

By Timothy R. Hughes, M. Marton, Allan R. Jones, C. J. Roberts, R. Stoughton, C. Armour, Holly A. Bennett, E. Coffey, Hongyue Dai, Yudong He and 12 more. Cell, 2000

2,743 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4fb78789f4baac06759c1fe6e92f673ebbe44e4d

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Citations in the corpus

Assessing Gene Significance from cDNA Microarray Expression Data via Mixed Models (2001, methodology): “² be used to construct genome-wide quantitative summary measures (Klus et al., 2000) and similarity pro les (Hughes et al., 2000).”
Daphnia as an emerging model for toxicological genomics (2008, methodology): “Other uses for mRNA abundance data include gene function discovery (Hughes et al., 2000; Shaw et al., 2007), genetic regulatory network analysis (Tavazoie et al., 1999), defining mechanisms of toxicity and clearance (Waring et al., 2001a, 2001b) and evaluating the effects of genetic and…”
Analyzing time series gene expression data (2004, background): “Many knockout expression experiments have been carried out in the static case (Hughes et al., 2000).”
Cotranscriptional set2 methylation of histone H3 lysine 36 recruits a repressive Rpd3 complex. (2005, positive): “NA Isolation and Microarray Analyses sogenic strains were grown in parallel in synthetic complete (SC) edium at 30°C, and RNA was prepared and extracted for microaray analyses as previously described (Hughes et al., 2000).”
Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks (2005, neutral): “Lovastatin Ergosterol biosynthesis42 Hmg2, Hmg1 Lipid metabolism (1, 10–4) BST1 (1), ERG1 (18), YSR3 (23), HMG2 (30), LCB5 (31), ERG13 (36), VRG4 (48)”
Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs (2005, methodology): “P values were calculated from a previously described error mode”
Genetics of gene expression surveyed in maize, mouse and man (2003, methodology): “Analysis of expression data Array images were scanned using the Agilent Dual Laser Microarray scanner ( Agilent Technologies ) and processed as previously describe”
Adaptive computation and machine learning (1998, background): “In the last couple of years a number of methods that do not rely on direct sequence similarity have been published [380, 162, 271, 378].”
Mycobacterium tuberculosis Pathogenesis and Molecular Determinants of Virulence (2003, result): “In DNA array analyses, since the levels of 4,000 genes are being compared usually as a ratio between two conditions or bacterial strains, many factors such as background noise (84) and statistical considerations (137, 161) may give erroneous results for the values obtained with specific genes.”
Colloquium: Criticality and dynamical scaling in living systems (2017, methodology): “…caused by single-gene knock-out experiments has been analyzed using empirical gene-expression data from the yeast (Saccharomyces cerevisae) (Hughes et al., 2000), with the conclusion that the best correspondence between empirical results and (RBN) model predictions is obtained for the…”
Relating whole-genome expression data with protein-protein interactions. (2002, methodology): “1998) and the Rosetta experiments (Hughes et al. 2000) in two protein complexes (the ribosome and the proteasome) as well as for the aggregated data sets (genetic, physical and yeast two-hybrid).”
Reverse engineering of regulatory networks in human B cells (2005, background): “, by large-scale gene knockouts or exogenous constraint”
The environmental stress response: a common yeast response to diverse environmental stresses (2003, background): “Consistently, many of the genes involved in tRNA processing, and almost all of the genes encoding cytosolic aminoacyl tRNA synthetases, are repressed as part of this program.”