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Updated: Nov 20, 2025

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
Published on: August 21, 2019
PrInCE: an R/Bioconductor package for protein-protein interaction network inference from co-fractionation mass
Michael A Skinnider1, Charley Cai1, R Greg Stacey1
1Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Summary:
We present PrInCE, an R/Bioconductor package that employs a machine-learning approach to infer protein-protein interaction networks from co-fractionation mass spectrometry (CF-MS) data. Previously distributed as a collection of Matlab scripts, our ground-up rewrite of this software package in an open-source language dramatically improves runtime and memory requirements. We describe several new features in the R implementation, including a test for the detection of co-eluting protein complexes and a method for differential network analysis. PrInCE is extensively documented and fully compatible with Bioconductor classes, ensuring it can fit seamlessly into existing proteomics workflows.
Availability And Implementation:
PrInCE is available from Bioconductor (https://www.bioconductor.org/packages/devel/bioc/html/PrInCE.html). Source code is freely available from GitHub under the MIT license (https://github.com/fosterlab/PrInCE). Support is provided via the GitHub issues tracker (https://github.com/fosterlab/PrInCE/issues).
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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