ArticleDatabase : the journal of biological databases and curation2020
Incorporation of a unified protein abundance dataset into the Saccharomyces genome database.
Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A screening pipeline to characterize stress-induced enzymes uncovers a cellular function for the poorly characterized alcohol dehydrogenase Bdh2.Journal of cell science · 2026Article
- The Saccharomyces Genome Database-a history of ideas and accomplishments, 1994-2026.FEMS yeast research · 2026Article
- A proteome-wide yeast degron collection for the dynamic study of protein function.The Journal of cell biology · 2025Article
- Saccharomyces genome database update: server architecture, pan-genome nomenclature, and external resources.Genetics · 2023Article
- A Suite of New Strain Construction Vectors for Gene Expression Knockdown in Budding Yeast.ACS synthetic biology · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
The identification and accurate quantitation of protein abundance has been a major objective of proteomics research. Abundance studies have the potential to provide users with data that can be used to gain a deeper understanding of protein function and regulation and can also help identify cellular pathways and modules that operate under various environmental stress conditions. One of the central missions of the Saccharomyces Genome Database (SGD; https://www.yeastgenome.org) is to work with researchers to identify and incorporate datasets of interest to the wider scientific community, thereby enabling hypothesis-driven research. A large number of studies have detailed efforts to generate proteome-wide abundance data, but deeper analyses of these data have been hampered by the inability to compare results between studies. Recently, a unified protein abundance dataset was generated through the evaluation of more than 20 abundance datasets, which were normalized and converted to common measurement units, in this case molecules per cell. We have incorporated these normalized protein abundance data and associated metadata into the SGD database, as well as the SGD YeastMine data warehouse, resulting in the addition of 56 487 values for untreated cells grown in either rich or defined media and 28 335 values for cells treated with environmental stressors. Abundance data for protein-coding genes are displayed in a sortable, filterable table on Protein pages, available through Locus Summary pages. A median abundance value was incorporated, and a median absolute deviation was calculated for each protein-coding gene and incorporated into SGD. These values are displayed in the Protein section of the Locus Summary page. The inclusion of these data has enhanced the quality and quantity of protein experimental information presented at SGD and provides opportunities for researchers to access and utilize the data to further their research.
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Registered trials
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