SynthesisNature methods2021
Meta-analysis defines principles for the design and analysis of co-fractionation mass spectrometry experiments.
Synthesis in Nature methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry.Nature communications · 2023Pooled it
- A tissue-specific atlas of protein-protein associations enables prioritization of candidate disease genes.Nature biotechnology · 2026Article
- ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning.Nature communications · 2026Article
- Mapping protein-metabolite interactions iniScience · 2025Article
- SEC-MX: an approach to systematically study the interplay between protein assembly states and phosphorylation.Nature communications · 2025Article
- Complete end-to-end learning from protein feature representation to protein interactome inference.GigaScience · 2025Article
- Progress in mass spectrometry approaches to profiling protein-protein interactions in the studies of the innate immune system.Journal of proteins and proteomics · 2024Article
- Alternative proteoforms and proteoform-dependent assemblies in humans and plants.Molecular systems biology · 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
- Deciphering protein interaction network dynamics with a machine learning-based framework.Nature methods · 2024Article
- Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts.Nature methods · 2024Article
- Hiding in plain sight: a research parasite's perspective on new lessons in old data.GigaScience · 2024Article
- Co-fractionation-mass spectrometry to characterize native mitochondrial protein assemblies in mammalian neurons and brain.Nature protocols · 2023Article
- HPC-Atlas: Computationally Constructing A Comprehensive Atlas of Human Protein Complexes.Genomics, proteomics & bioinformatics · 2023Article
- Next-generation proteomics for quantitative Jumbophage-bacteria interaction mapping.Nature communications · 2023Article
- Proteomic discovery of chemical probes that perturb protein complexes in human cells.Molecular cell · 2023Article
- Rapid Profiling of Protein Complex Reorganization in Perturbed Systems.Journal of proteome research · 2023Article
- Protein complexes in cells by AI-assisted structural proteomics.Molecular systems biology · 2023Article
- Discovering Protein-Protein Interactions using Co-Fractionation-Mass Spectrometry with Label-Free Quantitation.Methods in molecular biology (Clifton, N.J.) · 2023Article
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2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Co-fractionation mass spectrometry (CF-MS) has emerged as a powerful technique for interactome mapping. However, there is little consensus on optimal strategies for the design of CF-MS experiments or their computational analysis. Here, we reanalyzed a total of 206 CF-MS experiments to generate a uniformly processed resource containing over 11 million measurements of protein abundance. We used this resource to benchmark experimental designs for CF-MS studies and systematically optimize computational approaches to network inference. We then applied this optimized methodology to reconstruct a draft-quality human interactome by CF-MS and predict over 700,000 protein-protein interactions across 27 eukaryotic species or clades. Our work defines new resources to illuminate proteome organization over evolutionary timescales and establishes best practices for the design and analysis of CF-MS studies.
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34211188What Socratic holds
Registered trials
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 Socratic graph.