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) |
|---|---|
| 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
- Statistics and Probability
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics