Referenced datasets may contain one or more condition(s), and as a result there may be a greater number of conditions than datasets represented in a single clickable histogram bar. The histogram division at 0.0 separates the down-regulated (green) conditions and datasets from those that are up-regulated (red). Datasets are assigned one or more categories to facilitate grouping, filtering and browsing. Expression data are derived from records contained in the Gene Expression Omnibus, and are first log2 transformed and normalized. The PCL files generated for each dataset are used to populate the expression analysis tool SPELL.
No expression data for YPL025C.
View genes with similar expression profiles using SPELL (Serial Pattern of Expression Levels Locator).
Datasets are used to populate the expression analysis tool SPELL and may contain data for more than one unique experimental condition. All data is log2 transformed and normalized, and the files are provided in PCL format. Short descriptions of the experimental focus are provided, as are categories, assigned based on the area(s) of biology investigated and used in SPELL to group and filter like data. The number of unique experimental conditions are indicated and all datasets are referenced.
108 datasets for 76 referencesIncrease the total number of rows displayed on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table; download this table as a .txt file using the Download button;
Dataset | Description | Keywords | Number of Conditions | Reference |
---|---|---|---|---|
A Quantitative, High-Throughput Reverse Genetic Screen Reveals Novel Connections Between pre-mRNA Splicing and 5__ and 3__ end Transcript Determinants | The coding portions of most eukaryotic genes are interrupted by non-coding regions termed introns that must be excised prior to their translation | mRNA processing | 64 | Albulescu LO, et al. (2012) PMID:22479188 |
abf1-1 mutant at 36C | abf1-1 mutant and wt cells grown at 30C, raised to 36C for 45 min | transcription | 4 | Miyake T, et al. (2004) PMID:15192094 |
Aging in yeast | wt & sgs1 null, w/ or w/o MMS (DNA damaging agent) | DNA damage stimulus, stress | 8 | Fry RC, et al. (2003) PMID:12875747 |
Cell cycle, alpha-factor block-release | Culture synchronized by alpha factor arrest, then samples taken every 7 minutes as cells went through cell cycle. | mitotic cell cycle | 16 | Spellman PT, et al. (1998) PMID:9843569 |
Cell cycle, cdc15 block-release | Culture synchronized in telophase by arrest of cdc15 temperature-sensitive mutant | mitotic cell cycle | 25 | Spellman PT, et al. (1998) PMID:9843569 |
Cell cycle, elutriation | Culture synchronized by elutriation and samples removed at several time points up to 6.5 h. | mitotic cell cycle | 14 | Spellman PT, et al. (1998) PMID:9843569 |
Chitin synthesis | wt and fks1 mutant exposed to chitin-inducing glucosamine for 2-hours or continuous steady state | cell wall organization, chemical stimulus, stress | 11 | Bulik DA, et al. (2003) PMID:14555471 |
Comparative transcriptomic analysis between a high and a low sulfite producers wine yeast strains | The goal of this study was to compare the expression level of the whole genome of two wine yeast strains highly differing in their sulfite production (High producer strain: 10281A; Low producer strain: 1764A) | fermentation, sulfur utilization | 2 | Noble J, et al. (2015) PMID:25947166 |
Comparison of limitation by Ura, Sul, Pho, and Leu | Physiological response to limitation by diverse nutrients in steady-state (chemostat) cultures of S. cerevisiae | amino acid utilization, nutrient utilization, phosphorus utilization, sulfur utilization | 24 | Saldanha AJ, et al. (2004) PMID:15240820 |
Copper regulon | Growth conditions of excess copper or copper deficiency, regulated by Mac1 or Ace1 transcriptional activators. | cellular ion homeostasis, metal or metalloid ion stress | 6 | Gross C, et al. (2000) PMID:10922376 |
This diagram displays a gene network based on correlated expression profiles (purple lines) between the given gene (yellow circle) and genes that share expression profiles (gray circles). The correlation coefficient is calculated between every pair of genes in every dataset, then the number of datasets in which the pair of genes has a significant correlation with one another is determined. The network displays the genes whose expression is correlated with the given gene in the largest number of datasets. Please note that SPELL use a different algorithm to make a global calculation taking into account all the datasets at once, and may therefore display a different set of correlated genes.
Click on a gene to go to its specific page within SGD; drag any of the gene objects around within the visualization for easier viewing. Filter similar genes by adjusting the number of datasets in which their expression profiles are highly correlated with the gene of interest by clicking anywhere on the slider bar or dragging the tab to the desired filter number. Click “Reset” to automatically redraw the diagram.