Abstract
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.
Original language | English (US) |
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Pages (from-to) | 2775-2777 |
Number of pages | 3 |
Journal | Bioinformatics |
Volume | 37 |
Issue number | 17 |
DOIs | |
State | Published - Sep 1 2021 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Computational Mathematics
- Molecular Biology
- Biochemistry
- Statistics and Probability
- Computer Science Applications
- Computational Theory and Mathematics