ArticleNature communications2019
Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 36 papers.
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
36 citing papers in PubMed.
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- Computational analysis of the structural and functional impact of the deleterious nsSNPs in the humanBiochemistry and biophysics reports · 2026Article
- Network Analysis to Identify MicroRNAs Involved in Alzheimer's Disease and to Improve Drug Prioritization.Biomedicines · 2026Article
- A guide to building the matrisome interactome: from computational predictions to experimental validation.The FEBS journal · 2026Review
- Mining Alzheimer's Interactomes, Macromolecular Complexes and Pathways for Drug Discovery.Proteomics · 2025Review
- What Have Data Standards Ever Done for Us?Molecular & cellular proteomics : MCP · 2025Review
- Death-associated protein kinase 3 modulates migration and invasion of triple-negative breast cancer cells.PNAS nexus · 2024Article
- Comparison of colostrum and milk extracellular vesicles small RNA cargo in water buffalo.Scientific reports · 2024Article
- The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study.Database : the journal of biological databases and curation · 2023Article
- UniProt: the Universal Protein Knowledgebase in 2023.Nucleic acids research · 2023Article
- Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations.Research (Washington, D.C.) · 2023Article
- Resources and tools for rare disease variant interpretation.Frontiers in molecular biosciences · 2023Review
- Predicting functional consequences of mutations using molecular interaction network features.Human genetics · 2022Article
- CFTR interactome mapping using the mammalian membrane two-hybrid high-throughput screening system.Molecular systems biology · 2022Article
- The IntAct database: efficient access to fine-grained molecular interaction data.Nucleic acids research · 2022Article
- IID 2021: towards context-specific protein interaction analyses by increased coverage, enhanced annotation and enrichment analysis.Nucleic acids research · 2022Article
- Transcriptomic Characterization of Cow, Donkey and Goat Milk Extracellular Vesicles Reveals Their Anti-Inflammatory and Immunomodulatory Potential.International journal of molecular sciences · 2021Article
- Protein-protein interactions: Methods, databases, and applications in virus-host study.World journal of virology · 2021Review
- A protein interaction landscape of breast cancer.Science (New York, N.Y.) · 2021Article
- Analysing the yeast complexome-the Complex Portal rising to the challenge.Nucleic acids research · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
17 authors.
Funding
Abstract
The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule's interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release.
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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 OpenQuestion graph.