ArticleeLife2016
A computational interactome and functional annotation for the human proteome.
Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 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
- Complex assembly and activity states as multifaceted protein attributes explaining phenotypic variability.Molecular systems biology · 2026Article
- PrePPI - Structure-based Prediction of Protein-protein Interactomes and Networks.Journal of molecular biology · 2026Article
- Proteome-wide prediction of interactions between structured domains and peptide motifs reveals functionally coherent subnetworks.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks.Nature communications · 2026Article
- Complex Assembly and Activity States as Multifaceted Protein Attributes Explaining Phenotypic Variability.bioRxiv : the preprint server for biology · 2025Article
- Recent progress and future challenges in structure-based protein-protein interaction prediction.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Review
- Towards an interpretable deep learning model of cancer.NPJ precision oncology · 2025Review
- ZEPPI: Proteome-scale sequence-based evaluation of protein-protein interaction models.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- The Glycosaminoglycan Side Chains and Modular Core Proteins of Heparan Sulphate Proteoglycans and the Varied Ways They Provide Tissue Protection by Regulating Physiological Processes and Cellular Behaviour.International journal of molecular sciences · 2023Review
- Missense3D-PPI: A Web Resource to Predict the Impact of Missense Variants at Protein Interfaces Using 3D Structural Data.Journal of molecular biology · 2023Article
- PrePPI: A Structure Informed Proteome-wide Database of Protein-Protein Interactions.Journal of molecular biology · 2023Article
- PrePCI: A structure- and chemical similarity-informed database of predicted protein compound interactions.Protein science : a publication of the Protein Society · 2023Article
- Computational Methods and Deep Learning for Elucidating Protein Interaction Networks.Methods in molecular biology (Clifton, N.J.) · 2023Article
- PEPPI: Whole-proteome Protein-protein Interaction Prediction through Structure and Sequence Similarity, Functional Association, and Machine Learning.Journal of molecular biology · 2022Article
- Physicochemical classification of organisms.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Disease-specific interactome alterations via epichaperomics: the case for Alzheimer's disease.The FEBS journal · 2022Review
- Revealing protein-protein interactions at the transcriptome scale by sequencing.Molecular cell · 2021Article
- Discovery-Versus Hypothesis-Driven Detection of Protein-Protein Interactions and Complexes.International journal of molecular sciences · 2021Review
- Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.Briefings in bioinformatics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein's function. We provide annotations for most human proteins, including many annotated as having unknown function.
Indexed as
Identifiers
What 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.