YESdb: integrative analysis of environmental stress in yeast.


Journal

Database : the journal of biological databases and curation
ISSN: 1758-0463
Titre abrégé: Database (Oxford)
Pays: England
ID NLM: 101517697

Informations de publication

Date de publication:
01 01 2019
Historique:
received: 30 07 2018
revised: 30 01 2019
accepted: 31 01 2019
entrez: 2 3 2019
pubmed: 2 3 2019
medline: 25 7 2019
Statut: ppublish

Résumé

The stress response in the model organisms Saccharomyces cerevisiae is a well-studied system for which many data sets are available. Already in 2000, it was discovered that yeast cells trigger a similar transcriptional response when different types of stress are applied. However, the exact regulatory mechanisms and differences between the different types of stress are still not understood. Here, we present the Yeast Environmental Stress database (YESdb), a database containing all high-throughput experiments measuring various kinds of stress in yeast. The goal of the database is to allow the user to execute complex, integrative analyses of selected data sets, e.g. the comparison of measurements of the same stress using different platforms or differences between strains, stress strengths or types of stress. The analyses can be visualized in various ways and can be compiled into interactive reports to summarize and communicate the results. The data sets are available as differential conditions (typically stressed vs control), which are grouped to time or concentration series when multiple measurements over time or concentrations are done in one experiment. An annotation ontology has been constructed to annotate the data sets with the type, duration and strength of the applied stress, the used strain and experimental platform as well as the publication date. These annotations can easily be combined to select all relevant data sets for an analysis. YESdb allows to construct and execute Petri net-based workflows to perform predefined and custom analyses. E.g. to compare two types of stress (e.g. salt vs oxidative stress), the corresponding data sets are selected from the database, the consistently changed genes are defined and combined and the shared genes are characterized by enrichment analysis. A broad collection of visualizations is available most of which are also interactive. The results of all analyses can be summarized in an interactive report. Visualizations of individual steps (transitions) of YESdb workflows can be automatically added to this report or customized visualizations as well as interpretive text can manually be added to the report. Overall, YESdb aims at making all published data sets on yeast stress immediately available and comparable for integrated analysis of data sets and sets of genes in order to identify and assess hypotheses and mechanisms.

Identifiants

pubmed: 30821814
pii: 5367260
doi: 10.1093/database/baz023
pmc: PMC6396637
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press.

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Auteurs

Evi Berchtold (E)

Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, Amalienstraße, München, Germany.

Gergely Csaba (G)

Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, Amalienstraße, München, Germany.

Ralf Zimmer (R)

Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, Amalienstraße, München, Germany.

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Classifications MeSH