ArticleJournal of cell communication and signaling2024
Proteome-wide assessment of human interactome as a source of capturing domain-motif and domain-domain interactions.
Article in Journal of cell communication and signaling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Predicting Motif-Mediated Interactions Based on Viral Genomic Composition.International journal of molecular sciences · 2025Article
- Exploring Viral-Host Protein Interactions as Antiviral Therapies: A Computational Perspective.Microorganisms · 2024Review
- Prediction of virus-host interactions and identification of hot spot residues of DENV-2 and SH3 domain interactions.Archives of microbiology · 2024Article
- Prediction of motif-mediated viral mimicry through the integration of host-pathogen interactions.Archives of microbiology · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
Protein-protein interactions (PPIs) play a crucial role in various biological processes by establishing domain-motif (DMI) and domain-domain interactions (DDIs). While the existence of real DMIs/DDIs is generally assumed, it is rarely tested; therefore, this study extensively compared high-throughput methods and public PPI repositories as sources for DMI and DDI prediction based on the assumption that the human interactome provides sufficient data for the reliable identification of DMIs and DDIs. Different datasets from leading high-throughput methods (Yeast two-hybrid [Y2H], Affinity Purification coupled Mass Spectrometry [AP-MS], and Co-fractionation-coupled Mass Spectrometry) were assessed for their ability to capture DMIs and DDIs using known DMI/DDI information. High-throughput methods were not notably worse than PPI databases and, in some cases, appeared better. In conclusion, all PPI datasets demonstrated significant enrichment in DMIs and DDIs (
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Registered trials
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