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Updated: Jul 17, 2026

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Temporal Quantification of MAPK Induced Expression in Single Yeast Cells
Published on: October 4, 2013
Understanding signaling in yeast: Insights from network analysis.
K Yalçin Arga1, Z Ilsen Onsan, Betül Kirdar
1Department of Chemical Engineering, Boğaziçi University, 34342 Istanbul, Turkey.
Biotechnology and Bioengineering
|January 26, 2007
Summary
This study introduces a new method to build protein interaction networks for understanding cell signaling. The approach successfully identifies known and new proteins in yeast signaling pathways.
Area of Science:
- Systems Biology
- Computational Biology
- Molecular Biology
Background:
- Protein interaction networks are crucial for understanding cellular functions and signal transduction.
- Quantitative studies of signaling pathways require accurate network reconstruction.
Purpose of the Study:
- To develop a novel approach for reconstructing highly correlated protein interaction networks.
- To identify unknown components within signaling pathways by integrating diverse biological data.
- To reconstruct specific signaling sub-networks in yeast Saccharomyces cerevisiae.
Main Methods:
- Integration of protein-protein interaction data, gene expression data, and Gene Ontology annotations.
- Development of a novel algorithm for reconstructing highly correlated protein interaction networks.
- Application of Receiver Operating Characteristic (ROC) curve analysis to assess reconstruction efficiency.
- Identification and scoring of linear pathways to reconstruct specific sub-networks.
Main Results:
- Successfully reconstructed protein interaction networks in yeast Saccharomyces cerevisiae.
- Identified known components and novel candidate proteins for glucose-induction and high osmolarity MAPK signaling pathways.
- Demonstrated high efficiency and accuracy of the reconstruction algorithm via ROC analysis.
- Reconstructed two model pathways, highlighting the utility of the integrated approach.
Conclusions:
- The integrated approach is effective for predicting new signaling pathways.
- The method successfully identifies unknown members of documented signaling pathways.
- The approach aids in identifying functional network modules and their components.
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