de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Impressum Kontakt Einloggen
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Hochschulschrift

Modeling signal transduction pathways and their transcriptional response

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50545

Szczurek,  Ewa
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)

Sczcurek_Ewa_Diss.pdf
(beliebiger Volltext), 4MB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Szczurek, E. (2011). Modeling signal transduction pathways and their transcriptional response. PhD Thesis, Freie Universität Berlin, Berlin.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-77AE-3
Zusammenfassung
This thesis is concerned with revealing regulation of gene expression. The basic motivation behind our work is that gene regulation can be better resolved when analyzed in a cellular context of the upstream signaling pathway and known regulatory targets. Our source of data are perturbation experiments, which are performed on pathway components and induce changes in gene expression. In such a way, they connect the signaling pathway to its downstream target genes. This chapter starts with an introduction to the cellular con- text considered in the thesis (section 1.1) and the principles of perturbation experiments (section 1.2). We end with a concise summary of three approaches that comprise this thesis. The approaches tackle various problems in the process of revealing context-speci c regulatory networks (section 1.3). We deal with di erential expression analysis of the per- turbation data, enhanced with known transcription factor targets serving as examples of di erential genes (chapter 2), pathway model-based planning of informative perturbation experiments (chapter 3), and nally, with deregulation analysis, i.e., comparing changes in gene regulation between two di erent cell populations (chapter 4).