Response of yeast cells to stress
Ontology highlight
ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
PROVIDER: GSE3812 | GEO | 2005/12/15
SECONDARY ACCESSION(S): PRJNA94019
REPOSITORIES: GEO
Similar Datasets
Project description:Stress experiments repeating Gasch et al.,2000 conditions (Mol Biol Cell. 2000 Dec;11(12):4241-57). For each set of conditions I compared a deletion mutant for a predicted transcription regulator with a congenic wt strain. Groups of assays that are related as part of a time series. Computed
2005-12-14 | E-GEOD-3812 | biostudies-arrayexpress
Project description:Stress experiments repeating Gasch et al.,2000 conditions. For each set of conditions I compared a deletion mutant for a predicted transcription regulator with a congenic wt strain.
2005-10-07 | E-SMDB-1822 | biostudies-arrayexpress
Project description:We explored genomic expression patterns in the yeast Saccharomyces cerevisiae responding to diverse environmental transitions. DNA microarrays were used to measure changes in transcript levels over time for almost every yeast gene, as cells responded to temperature shocks, hydrogen peroxide, the superoxide-generating drug menadione, the sulfhydryl-oxidizing agent diamide, the disulfide-reducing agent dithiothreitol, hyper- and hypo-osmotic shock, amino acid starvation, nitrogen source depletion, and progression into stationary phase. A large set of genes (approximately 900) showed a similar drastic response to almost all of these environmental changes. Additional features of the genomic responses were specialized for specific conditions. Promoter analysis and subsequent characterization of the responses of mutant strains implicated the transcription factors Yap1p, as well as Msn2p and Msn4p, in mediating specific features of the transcriptional response, while the identification of novel sequence elements provided clues to novel regulators. Physiological themes in the genomic responses to specific environmental stresses provided insights into the effects of those stresses on the cell. Study is described in more detail in Gasch AP et al.(2000) Mol Biol Cell 11:4241-57 Keywords: other
2002-02-12 | GSE18 | GEO
Project description:The arrays were used to study the effects of modifying phosphate levels in yeast, either through mutation, or chemical manipulation. This study is described in more detail in Ogawa N et al.(2000) Mol Biol Cell 11:4309-21 Keywords: other
2002-02-12 | GSE20 | GEO
Project description:HeLa mitotic cells were collected using a mitotic shakeoff apparatus to study gene expression in early G1 phase of the human cell cycle. This set includes microarray data from two shake-off experiments : shake 1 (0h-14h) which was conducted over 14 hours and RNA samples collected every 2 hrs, and shake 2 (0min-120min) which was conducted over 2 hours and samples collected every 15 minutes. Total RNA was prepared using ULTRASPEC RNA isolation system, and Reference RNA was extracted from asynchronously growing HeLa cells using TRIzol. For cDNA synthesis and microarray hybridization, refer to Whitfield ML. et al., Mol Biol Cell, 2002. 13(6): p. 1977-2000. Groups of assays that are related as part of a time series. Age: g1 progression after mitotic shake-off Replicate: two biological replicates (shake1 and shake2) Keywords: time_series_design
2009-02-26 | GSE12473 | GEO
Project description:HeLa mitotic cells were collected using a mitotic shakeoff apparatus to study gene expression in early G1 phase of the human cell cycle. This set includes microarray data from two shake-off experiments : shake 1 (0h-14h) which was conducted over 14 hours and RNA samples collected every 2 hrs, and shake 2 (0min-120min) which was conducted over 2 hours and samples collected every 15 minutes. Total RNA was prepared using ULTRASPEC RNA isolation system, and Reference RNA was extracted from asynchronously growing HeLa cells using TRIzol. For cDNA synthesis and microarray hybridization, refer to Whitfield ML. et al., Mol Biol Cell, 2002. 13(6): p. 1977-2000. Groups of assays that are related as part of a time series. Age: g1 progression after mitotic shake-off Replicate: two biological replicates (shake1 and shake2) Keywords: time_series_design Computed
2010-06-25 | E-GEOD-12473 | biostudies-arrayexpress
Project description:Schaner, M., et al.; Mol Biol Cell. 2003 Nov;14(11):4376-86. Figure 4 Clustering of breast and ovarian carcinoma cases. 68 breast and 57 ovarian cases were co-clustered to discern both similarities and disparities between the two sample sets. An ovarianspecific set of highly expressed transcripts was identified in comparison to breast across the 3363 transcripts. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
2006-02-25 | GSE4268 | GEO
Project description:The arrays were used to study the effects of modifying phosphate levels in yeast, either through mutation, or chemical manipulation. This study is described in more detail in Ogawa N et al.(2000) Mol Biol Cell 11:4309-21
2002-02-11 | E-GEOD-20 | biostudies-arrayexpress
Project description:Schaner M., et al.; Mol Biol Cell. 2003 Nov;14(11):4376-86. Figure 1 Unsupervised hierarchical clustering of ovarian cell lines and ovarian cancers. Cell lines were not co-clustered with the tumor specimens, because these cell lines have a very prominent proliferation cluster (Perou et al., 1999; Ross et al., 2000) that significantly influences the clustering of the tumor samples if the two sample sets are not analyzed separately. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
2006-02-25 | GSE4198 | GEO
Project description:Schaner, M., et al.; Mol Biol Cell. 2003 Nov;14(11):4376-86. Figure 4 Clustering of breast and ovarian carcinoma cases. 68 breast and 57 ovarian cases were co-clustered to discern both similarities and disparities between the two sample sets. An ovarianspecific set of highly expressed transcripts was identified in comparison to breast across the 3363 transcripts. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Using regression correlation
2006-02-24 | E-GEOD-4268 | biostudies-arrayexpress