Model-based extension of high-throughput to high-content data |
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| Authors: | Andrea C Pfeifer Daniel Kaschek Julie Bachmann Ursula Klingmüller Jens Timmer |
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| Affiliation: | (1) Division Systems Biology of Signal Transduction, DKFZ-ZMBH Alliance, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany;(2) Bioquant, Heidelberg University, BioQuant Building, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany;(3) Physics Institute, University of Freiburg, Hermann-Herder-Strasse 3, 79104 Freiburg i.Br., Germany;(4) Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg, Albertstrasse 19, 79104 Freiburg i.Br., Germany |
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| Abstract: | Background High-quality quantitative data is a major limitation in systems biology. The experimental data used in systems biology can be assigned to one of the following categories: assays yielding average data of a cell population, high-content single cell measurements and high-throughput techniques generating single cell data for large cell populations. For modeling purposes, a combination of data from different categories is highly desirable in order to increase the number of observable species and processes and thereby maximize the identifiability of parameters. |
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