ArticleNucleic acids research2020
LIST-S2: taxonomy based sorting of deleterious missense mutations across species.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 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
60 citing papers in PubMed, 115 citations in OpenAlex.
- A Common Missense Variant, W335S, in β2-Glycoprotein I (APOH) is Associated with Increased Autoantibody Levels but Reduced Venous Thromboembolism Risk.medRxiv : the preprint server for health sciences · 2026Article
- EMMVEP: An Ensemble Method for Protein Missense Variant Effect Prediction Based on Multi-Source Feature Fusion.Interdisciplinary sciences, computational life sciences · 2026Article
- MissenseHMM: state-based annotations for missense variants through joint modeling of pathogenicity scores.bioRxiv : the preprint server for biology · 2026Article
- SomaMutDB 2.0: A comprehensive database for exploring somatic mutations and their functional impact in normal human tissues.Nucleic acids research · 2026Article
- DBP-CanPred: a machine learning model for predicting cancer-causing mutations in DNA-binding proteins.Frontiers in bioinformatics · 2026Article
- Precision diagnosis ofFrontiers in genetics · 2026Article
- Biological Context-Informed and Population-Stratified Strategies Improve Genetic Diagnosis of CCDC22-Related Disorder.Genetics research · 2026Article
- MutAnt: mutation annotation tool predicts deleteriousness of missense mutations and improves mutation calling from transcriptomics.Human genetics · 2025Article
- Calibrated Variant Effect Prediction at the Residue Level Using Conditional Score Distributions.bioRxiv : the preprint server for biology · 2025Article
- Computational Analysis ofACS chemical neuroscience · 2025Article
- Assessing variant effect predictors and disease mechanisms in intrinsically disordered proteins.PLoS computational biology · 2025Article
- Assessing the performance of 28 pathogenicity prediction methods on rare single nucleotide variants in coding regions.BMC genomics · 2025Article
- PRP: pathogenic risk prediction for rare nonsynonymous single nucleotide variants.Human genetics · 2025Article
- Leveraging transformers for semi-supervised pathogenicity prediction with soft labels.Journal of integrative bioinformatics · 2025Article
- Evaluating variant pathogenicity prediction tools to establish African inclusive guidelines for germline genetic testing.Communications medicine · 2025Article
- Missense variants pathogenicity annotation from homologous proteins.Bioinformatics (Oxford, England) · 2025Article
- Accurate identification and mechanistic evaluation of pathogenic missense variants withProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Galloway-mowat syndrome 3 (GAMOS3): a novel disease-causing variant in OSGEP gene and expansion of the clinical spectrum.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Article
- Incorporating genetic load contributes to predicting Arabidopsis thaliana's response to climate change.Nature communications · 2025Article
- DS-MVP: identifying disease-specific pathogenicity of missense variants by pre-training representation.Briefings in bioinformatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The separation of deleterious from benign mutations remains a key challenge in the interpretation of genomic data. Computational methods used to sort mutations based on their potential deleteriousness rely largely on conservation measures derived from sequence alignments. Here, we introduce LIST-S2, a successor to our previously developed approach LIST, which aims to exploit local sequence identity and taxonomy distances in quantifying the conservation of human protein sequences. Unlike its predecessor, LIST-S2 is not limited to human sequences but can assess conservation and make predictions for sequences from any organism. Moreover, we provide a web-tool and downloadable software to compute and visualize the deleteriousness of mutations in user-provided sequences. This web-tool contains an HTML interface and a RESTful API to submit and manage sequences as well as a browsable set of precomputed predictions for a large number of UniProtKB protein sequences of common taxa. LIST-S2 is available at: https://list-s2.msl.ubc.ca/.
Indexed as
Identifiers
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.