Computational processing and error reduction strategies for standardized quantitative data in biological networks.


High-quality quantitative data generated under standardized conditions is critical for understanding dynamic cellular processes. We report strategies for error reduction, and algorithms for automated data processing and for establishing the widely used techniques of immunoprecipitation and immunoblotting as highly precise methods for the quantification of protein levels and modifications. To determine the stoichiometry of cellular components and to ensure comparability of experiments, relative signals are converted to absolute values. A major source for errors in blotting techniques are inhomogeneities of the gel and the transfer procedure leading to correlated errors. These correlations are prevented by randomized gel loading, which significantly reduces standard deviations. Further error reduction is achieved by using housekeeping proteins as normalizers or by adding purified proteins in immunoprecipitations as calibrators in combination with criteria-based normalization. Additionally, we developed a computational tool for automated normalization, validation and integration of data derived from multiple immunoblots. In this way, large sets of quantitative data for dynamic pathway modeling can be generated, enabling the identification of systems properties and the prediction of targets for efficient intervention.


PubMed ID: 16336276

Projects: SBEpo - Systems Biology of Erythropoietin

Publication type: Journal

Journal: FEBS J

Citation: FEBS J. 2005 Dec;272(24):6400-11. doi: 10.1111/j.1742-4658.2005.05037.x.

Date Published: 13th Dec 2005

Registered Mode: Not specified

Authors: M. Schilling, T. Maiwald, S. Bohl, M. Kollmann, C. Kreutz, J. Timmer, U. Klingmuller

help Submitter

Views: 3700

Created: 25th Oct 2016 at 14:14

Last updated: 3rd Aug 2020 at 18:36

help Tags

This item has not yet been tagged.

help Attributions


Powered by
Copyright © 2008 - 2022 The University of Manchester and HITS gGmbH

By continuing to use this site you agree to the use of cookies