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Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation

External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analy...

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Hauptverfasser: Kowarsch, Andreas (VerfasserIn) , Blöchl, Florian (VerfasserIn) , Bohl, Sebastian (VerfasserIn) , Saile, Maria (VerfasserIn) , Gretz, Norbert (VerfasserIn) , Klingmüller, Ursula (VerfasserIn) , Theis, Fabian J. (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 30 November 2010
In: BMC bioinformatics
Year: 2010, Jahrgang: 11, Pages: 1-14
ISSN:1471-2105
DOI:10.1186/1471-2105-11-585
Online-Zugang:Resolving-System, kostenfrei, Volltext: https://doi.org/10.1186/1471-2105-11-585
Verlag, kostenfrei, Volltext: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-585
Volltext
Verfasserangaben:Andreas Kowarsch, Florian Blöchl, Sebastian Bohl, Maria Saile, Norbert Gretz, Ursula Klingmüller, Fabian J. Theis
Beschreibung
Zusammenfassung:External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analyses based on clustering or gene set enrichment only partly reveal this information, matrix factorization techniques are well suited for a detailed temporal analysis. In signal processing, factorization techniques incorporating data properties like spatial and temporal correlation structure have shown to be robust and computationally efficient. However, such correlation-based methods have so far not be applied in bioinformatics, because large scale biological data rarely imply a natural order that allows the definition of a delayed correlation function.
Beschreibung:Gesehen am 22.03.2023
Beschreibung:Online Resource
ISSN:1471-2105
DOI:10.1186/1471-2105-11-585

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