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

Date

Dec 5, 2013

Time

10:30 AM - 11:30 AM

Speaker

Katja Ickstadt

Affiliation

Technische Universität Dortmund

Series

IMB - Seminar

Language

de

Main Topic

Biologie

Other Topics

Biologie

Host

Ingo Roeder

Description

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.

Last modified: Dec 2, 2013, 1:41:40 PM