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Modelling signalling networks from perturbation data.

Mathurin Dorel1,2,3, Bertram Klinger1,2, Torsten Gross1,2

  • 1Institute of Pathology, Charité Universitätsmedizin, Berlin, Germany.

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|June 23, 2018
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Summary
This summary is machine-generated.

We developed STASNet, a new tool for analyzing complex cell signaling networks. It accurately models signaling pathways, revealing SHP2

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Molecular Biology

Background:

  • Intracellular signaling relies on complex networks, challenging to understand without models, especially with feedback loops.
  • Modular Response Analysis (MRA) is a useful method for studying these signaling networks.

Purpose of the Study:

  • To develop an advanced MRA-based software package for modeling signaling networks.
  • To apply this tool to investigate the role of SHP2 in colon cancer signaling.

Main Methods:

  • Developed STASNet (STeady-STate Analysis of Signalling Networks), an extended MRA software package.
  • Utilized incomplete perturbation schemes and multi-perturbation data for network modeling.
  • Applied STASNet to colon cancer cell line data (Widr and SHP2-depleted).

Main Results:

  • STASNet models demonstrated top-tier performance in network analysis.
  • SHP2 is essential for mitogen-activated protein kinase (MAPK) signaling.
  • AKT signaling partially depends on SHP2.

Conclusions:

  • STASNet provides a robust method for analyzing complex signaling networks.
  • SHP2 plays a critical role in MAPK signaling pathways relevant to colon cancer.