ArticleJournal of proteome research2024
FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe.
Article in Journal of proteome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Catechol-Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- ProteoMeter: a pipeline for integrating multi-PTM and limited proteolysis data to reveal modification-structure coupling at the residue level.NAR genomics and bioinformatics · 2026Article
- Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics.Journal of proteome research · 2026Article
- Limited Proteolysis Mass Spectrometry to Identify Protein Structural Differences in Brain Tissue.Bio-protocol · 2026Article
- Detecting misfolded non-covalent lasso entanglements in protein structures, simulation trajectories, and mass spectrometry data.bioRxiv : the preprint server for biology · 2026Article
- 3D Proteomics: Structural, Functional, Chemical and Biomarker Discovery Proteomics With LiP-MS.Molecular & cellular proteomics : MCP · 2026Review
- Chaperone dependency during biogenesis does not correlate with chaperone dependency during refolding.Molecular systems biology · 2026Article
- A widespread protein misfolding mechanism is differentially rescued in vitro by chaperones based on gene essentiality.Nature communications · 2025Article
- A shrinkage-based statistical method for testing group mean differences in quantitative bottom-up proteomics.BMC bioinformatics · 2025Article
- ATP-Driven Allosteric Regulation of 14-3-3: Positive Modulation of ATP Hydrolysis and Negative Regulation of Peptide Binding.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025Article
- A widespread protein misfolding mechanism is differentially rescued by chaperones based on gene essentiality.bioRxiv : the preprint server for biology · 2025Article
- Non-native entanglement protein misfolding observed in all-atom simulations and supported by experimental structural ensembles.Science advances · 2025Article
- Proteins with cognition-associated structural changes in a rat model of aging exhibit reduced refolding capacity.Science advances · 2025Article
- Chaperone Dependency during Primary Protein Biogenesis Does Not Correlate with Chaperone Dependency duringbioRxiv : the preprint server for biology · 2025Article
- Protein misfolding involving entanglements providesa structural explanation for the origin of stretched-exponential refolding kinetics.Science advances · 2025Article
- Analysis and Visualization of Quantitative Proteomics Data Using FragPipe-Analyst.Journal of proteome research · 2024Article
- Article
- Stability-based approaches in chemoproteomics.Expert reviews in molecular medicine · 2024Review
- Analysis and visualization of quantitative proteomics data using FragPipe-Analyst.bioRxiv : the preprint server for biology · 2024Article
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Abstract
Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.