ArticlePLoS computational biology2016
Predicted Molecular Effects of Sequence Variants Link to System Level of Disease.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
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Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- Embeddings from protein language models predict conservation and variant effects.Human genetics · 2022Article
- Mapping OMIM Disease-Related Variations on Protein Domains Reveals an Association Among Variation Type, Pfam Models, and Disease Classes.Frontiers in molecular biosciences · 2021Article
- Protein-protein and protein-nucleic acid binding residues important for common and rare sequence variants in human.BMC bioinformatics · 2020Article
- Variant effect predictions capture some aspects of deep mutational scanning experiments.BMC bioinformatics · 2020Article
- Predicting pathogenicity of missense variants with weakly supervised regression.Human mutation · 2019Article
- Fido-SNP: the first webserver for scoring the impact of single nucleotide variants in the dog genome.Nucleic acids research · 2019Article
- Missense variant pathogenicity predictors generalize well across a range of function-specific prediction challenges.Human mutation · 2017Article
- Common sequence variants affect molecular function more than rare variants?Scientific reports · 2017Article
- Protein function in precision medicine: deep understanding with machine learning.FEBS letters · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Developments in experimental and computational biology are advancing our understanding of how protein sequence variation impacts molecular protein function. However, the leap from the micro level of molecular function to the macro level of the whole organism, e.g. disease, remains barred. Here, we present new results emphasizing earlier work that suggested some links from molecular function to disease. We focused on non-synonymous single nucleotide variants, also referred to as single amino acid variants (SAVs). Building upon OMIA (Online Mendelian Inheritance in Animals), we introduced a curated set of 117 disease-causing SAVs in animals. Methods optimized to capture effects upon molecular function often correctly predict human (OMIM) and animal (OMIA) Mendelian disease-causing variants. We also predicted effects of human disease-causing variants in the mouse model, i.e. we put OMIM SAVs into mouse orthologs. Overall, fewer variants were predicted with effect in the model organism than in the original organism. Our results, along with other recent studies, demonstrate that predictions of molecular effects capture some important aspects of disease. Thus, in silico methods focusing on the micro level of molecular function can help to understand the macro system level of disease.
Indexed as
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What OpenQuestion 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 OpenQuestion graph.