Nonparametric Bayesian models uncover distinct connections between the same proteins in heterogenous cell populations

Datum

05.12.2013

Zeit

10:30 - 11:30

Sprecher

Katja Ickstadt

Zugehörigkeit

Technische Universität Dortmund

Serie

IMB - Seminar

Sprache

de

Hauptthema

Biologie

Andere Themen

Biologie

Host

Ingo Roeder

Beschreibung

Cell biology research is fundamentally limited by the number ofintracellular components, particularly proteins, that can be co-measured in the same cell. Therefore, cell-to-cell heterogeneity in unmeasured proteins can lead to completely different functional relations between the same measured proteins. Attempts to infer such relations in a heterogeneous cell population can yield meaningless averages if only one underlying biochemical network is assumed. To address this, we developed a method that couples an iterative unmixing process with a Bayesian analysis for each unmixed subpopulation. The approach enables to identify the number of distinct cell subpopulations, unmix their corresponding observations and resolve the network structure of each subpopulation. Using simulations of the MAPK pathway upon EGF and NGF stimulations we demonstrate and assess the method's performance and discuss the implications of the concept and method to systems biology.

Letztmalig verändert: 02.12.2013, 13:41:40