Saccharomyces cerevisiae
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA128783 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Absolute expression level of Saccharomyces paradoxus genes
| PRJNA128791 | ENA
Project description:Absolute expression level of Saccharomyces bayanus genes
| PRJNA128785 | ENA
Project description:Absolute expression level of Saccharomyces mikatae genes
| PRJNA128807 | ENA
Project description:Saccharomyces cerevisiae is an excellent microorganism for industrial succinic acid production, but high succinic acid concentration will inhibit the growth of Saccharomyces cerevisiae then reduce the production of succinic acid. Through analysis the transcriptomic data of Saccharomyces cerevisiae with different genetic backgrounds under different succinic acid stress, we hope to find the response mechanism of Saccharomyces cerevisiae to succinic acid.
2022-01-09 | GSE193190 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE22191: Absolute expression level of Debaryomyces hansenii genes GSE22192: Absolute expression level of Yarrowia lipolytica genes GSE22193: Absolute expression level of Saccharomyces paradoxus genes GSE22194: Absolute expression level of Candida glabrata genes GSE22197: Absolute expression level of Candida albicans genes GSE22198: Absolute expression level of Kluyveromyces lactis genes GSE22199: Absolute expression level of Kluyveromyces waltii genes GSE22200: Absolute expression level of Saccharomyces castellii genes GSE22201: Absolute expression level of Saccharomyces mikatae genes GSE22202: Absolute expression level of Saccharomyces kluyveryii genes GSE22204: Absolute expression level of Saccharomyces cerevisiae genes GSE22205: Absolute expression level of Saccharomyces bayanus genes GSE22211: Genome-wide nucleosome position data for 12 yeast species Refer to individual Series
2010-07-05 | E-GEOD-21960 | biostudies-arrayexpress
Project description:<p><em>Saccharomyces cerevisiae</em> is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of <em>S. cerevisiae</em> by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis.</p>
2022-08-31 | MTBLS697 | MetaboLights
Project description:MCT1 was deleted in Saccharomyces cerevisiae and gene expression was measured over a timecourse.
2020-06-02 | GSE151606 | GEO
Project description:Comparative Genomic Hybridization of natural Saccharomyces cerevisiae strains vs lab reference strains.
2020-12-31 | GSE136466 | GEO
Project description:A six array study using total gDNA recovered from two separate cultures of each of three different strains of Saccharomyces cerevisiae (YB-210 or CRB, Y389 or MUSH, and Y2209 or LEP) and two separate cultures of Saccharomyces cerevisiae DBY8268. Each array measures the hybridization of probes tiled across the Saccharomyces cerevisiae genome.
2014-10-01 | GSE56441 | GEO
Project description:Industrial bioethanol production may involve a low pH environment,improving the tolerance of S. cerevisiae to a low pH environment caused by inorganic acids may be of industrial importance to control bacterial contamination, increase ethanol yield and reduce production cost. Through analysis the transcriptomic data of Saccharomyces cerevisiae with different ploidy under low pH stress, we hope to find the tolerance mechanism of Saccharomyces cerevisiae to low pH.
2022-12-09 | GSE210964 | GEO