ArticleNature methods2021
PCprophet: a framework for protein complex prediction and differential analysis using proteomic data.
Article in Nature methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis defines principles for the design and analysis of co-fractionation mass spectrometry experiments.Nature methods · 2021Pooled it
- PCIPG: A comprehensive framework for protein complex identification based on a probabilistic graphical model.PLoS computational biology · 2026Article
- The complexome contextualizes proteomics data to fingerprint biological states and highlight perturbed functional modules in disease.NPJ systems biology and applications · 2026Article
- Emerging approaches for characterizing spatial and temporal dynamics of pathogen-induced organelle remodeling.Cell systems · 2026Review
- Article
- Integrating Proteomics into Personalized Medicine for Inflammatory Bowel Disease-Reality or Challenge?International journal of molecular sciences · 2025Review
- Integrating CORUM and co-fractionation mass spectrometry to create enhanced benchmarks for protein complex predictions.Briefings in bioinformatics · 2025Article
- Progress toward a comprehensive brain protein interactome.Biochemical Society transactions · 2025Review
- SEC-MX: an approach to systematically study the interplay between protein assembly states and phosphorylation.Nature communications · 2025Article
- XYLAN O-ACETYLTRANSFERASE 6 promotes xylan synthesis by forming a complex with IRX10 and governs wall formation in rice.The Plant cell · 2024Article
- Large-scale map of RNA-binding protein interactomes across the mRNA life cycle.Molecular cell · 2024Article
- Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications.Journal of hematology & oncology · 2024Review
- Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes.Annual review of biomedical data science · 2024Review
- Systematic identification of structure-specific protein-protein interactions.Molecular systems biology · 2024Article
- Integration of protein sequence and protein-protein interaction data by hypergraph learning to identify novel protein complexes.Briefings in bioinformatics · 2024Article
- Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry.Journal of proteome research · 2024Article
- DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes.Nature methods · 2024Article
- Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts.Nature methods · 2024Article
- Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation.Nature communications · 2023Article
- Next-generation proteomics for quantitative Jumbophage-bacteria interaction mapping.Nature communications · 2023Article
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the availability of methods for analyzing protein complexes, systematic analysis of complexes under multiple conditions remains challenging. Approaches based on biochemical fractionation of intact, native complexes and correlation of protein profiles have shown promise. However, most approaches for interpreting cofractionation datasets to yield complex composition and rearrangements between samples depend considerably on protein-protein interaction inference. We introduce PCprophet, a toolkit built on size exclusion chromatography-sequential window acquisition of all theoretical mass spectrometry (SEC-SWATH-MS) data to predict protein complexes and characterize their changes across experimental conditions. We demonstrate improved performance of PCprophet over state-of-the-art approaches and introduce a Bayesian approach to analyze altered protein-protein interactions across conditions. We provide both command-line and graphical interfaces to support the application of PCprophet to any cofractionation MS dataset, independent of separation or quantitative liquid chromatography-MS workflow, for the detection and quantitative tracking of protein complexes and their physiological dynamics.
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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.