ArticleProceedings of the National Academy of Sciences of the United States of America2011
Modular coherence of protein dynamics in yeast cell polarity system.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- Polarization as a Process: The Potential of Process Ontology for Understanding Cellular Symmetry Breaking.BioEssays : news and reviews in molecular, cellular and developmental biology · 2026Review
- Oligomerization-dependent and synergistic regulation of Cdc42 GTPase cycling by a GEF and a GAP.EMBO reports · 2026Article
- Review
- A nonparametric significance test for sampled networks.Bioinformatics (Oxford, England) · 2018Article
- ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.PloS one · 2014Article
- Spatially distinct functions of Clb2 in the DNA damage response.Cell cycle (Georgetown, Tex.) · 2014Article
- A fluorescent reporter for mapping cellular protein-protein interactions in time and space.Molecular systems biology · 2013Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
In this study, we investigated on a systems level how complex protein interactions underlying cell polarity in yeast determine the dynamic association of proteins with the polar cortical domain (PCD) where they localize and perform morphogenetic functions. We constructed a network of physical interactions among >100 proteins localized to the PCD. This network was further divided into five robust modules correlating with distinct subprocesses associated with cell polarity. Based on this reconstructed network, we proposed a simple model that approximates a PCD protein's molecular residence time as the sum of the characteristic time constants of the functional modules with which it interacts, weighted by the number of edges forming these interactions. Regression analyses showed excellent fitting of the model with experimentally measured residence times for a large subset of the PCD proteins. The model is able to predict residence times using small training sets. Our analysis also revealed a scaffold protein that imposes a local constraint of dynamics for certain interacting proteins.
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Registered trials
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