Bernhard Steiert

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About Bernhard Steiert:

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SEEK ID: https://fairdomhub.org/people/771

Location: Germany

ORCID: Not specified

Joined: 9th Jan 2017

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e:Bio

e:Bio - Innovations Competition Systems Biology

Projects: SulfoSys - Biotec, SBEpo - Systems Biology of Erythropoietin

Web page: http://www.fona.de/en/14276

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SBEpo - Systems Biology of Erythropoietin

Multi-level mathematical modeling of erythropoiesis for optimized expansion of erythroid progenitor cells and improved treatment regimes

Programme: e:Bio

Public web page: Not specified

Organisms: Homo sapiens, Mus musculus

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University of Freiburg

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Country: Germany

City: Freiburg

Web page: http://www.uni-freiburg.de/

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WP1: Integration of Epo-induced Signal Transduction

SBEpo - Systems Biology of Erythropoietin

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Submitter: Maja Rey

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Created: 11th Oct 2016 at 09:24

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L1 regularization facilitates detection of cell type-specific parameters in dynamical systems

SBEpo - Systems Biology of Erythropoietin

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MOTIVATION: A major goal of drug development is to selectively target certain cell types. Cellular decisions influenced by drugs are often dependent on the dynamic processing of information. Selective …

Authors: B. Steiert, J. Timmer, C. Kreutz

Date Published: 3rd Sep 2016

Publication Type: Not specified

PubMed ID: 27587694

Citation: Bioinformatics. 2016 Sep 1;32(17):i718-i726. doi: 10.1093/bioinformatics/btw461.

Created: 9th Jan 2017 at 11:04, Last updated: 8th Dec 2022 at 17:26

Driving the Model to Its Limit: Profile Likelihood Based Model Reduction

SBEpo - Systems Biology of Erythropoietin

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In systems biology, one of the major tasks is to tailor model complexity to information content of the data. A useful model should describe the data and produce well-determined parameter estimates and …

Authors: T. Maiwald, H. Hass, B. Steiert, J. Vanlier, R. Engesser, A. Raue, F. Kipkeew, H. H. Bock, D. Kaschek, C. Kreutz, J. Timmer

Date Published: 3rd Sep 2016

Publication Type: Not specified

PubMed ID: 27588423

Citation: PLoS One. 2016 Sep 2;11(9):e0162366. doi: 10.1371/journal.pone.0162366. eCollection 2016.

Created: 9th Jan 2017 at 11:06, Last updated: 8th Dec 2022 at 17:26

Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells.

SBEpo - Systems Biology of Erythropoietin

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Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs … such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.

Authors: R. Merkle, B. Steiert, F. Salopiata, S. Depner, A. Raue, N. Iwamoto, M. Schelker, H. Hass, M. Wasch, M. E. Bohm, O. Mucke, D. B. Lipka, C. Plass, W. D. Lehmann, C. Kreutz, J. Timmer, M. Schilling, U. Klingmuller

Date Published: 6th Aug 2016

Publication Type: Journal

PubMed ID: 27494133

Citation: PLoS Comput Biol. 2016 Aug 5;12(8):e1005049. doi: 10.1371/journal.pcbi.1005049. eCollection 2016 Aug.

Created: 13th Dec 2016 at 09:42, Last updated: 8th Dec 2022 at 17:26

Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.

SBEpo - Systems Biology of Erythropoietin

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UNLABELLED: Modeling of dynamical systems using ordinary differential equations is a popular approach in the field of systems biology. Two of the most critical steps in this approach are to construct …

Authors: A. Raue, B. Steiert, M. Schelker, C. Kreutz, T. Maiwald, H. Hass, J. Vanlier, C. Tonsing, L. Adlung, R. Engesser, W. Mader, T. Heinemann, J. Hasenauer, M. Schilling, T. Hofer, E. Klipp, F. Theis, U. Klingmuller, B. Schoberl, J. Timmer

Date Published: 1st Nov 2015

Publication Type: Journal

PubMed ID: 26142188

Citation: Bioinformatics. 2015 Nov 1;31(21):3558-60. doi: 10.1093/bioinformatics/btv405. Epub 2015 Jul 3.

Created: 13th Oct 2016 at 10:03, Last updated: 8th Dec 2022 at 17:26

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