ArticleNature communications2023
Deep structured learning for variant prioritization in Mendelian diseases.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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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
32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- Deep learning approaches for resolving genomic discrepancies in cancer: a systematic review and clinical perspective.Briefings in bioinformatics · 2025Pooled it
- A systematic review on the generative AI applications in human medical genetics.Frontiers in genetics · 2025Pooled it
- Convergent human genetic evidence implicates serine biosynthesis in diabetic peripheral neuropathy.medRxiv : the preprint server for health sciences · 2026Article
- HeterozygousJIMD reports · 2026Article
- MENDELSEEK: An algorithm that predicts mendelian genes and elucidates what makes them special.PLoS computational biology · 2026Article
- The continued promise of genomic technologies and software in neurogenetics.Journal of neuromuscular diseases · 2025Review
- Current perspectives and challenges of using artificial intelligence in immunodeficiencies.The Journal of allergy and clinical immunology · 2025Review
- Role of multi-omics in aquaculture genetics and breeding: current status and future perspective.Science China. Life sciences · 2025Review
- Clinical and data-driven optimization of Genomiser for rare disease patients: experience from the Hong Kong Genome Project.Briefings in bioinformatics · 2025Article
- Increasing pathogenic germline variant diagnosis rates in precision medicine: current best practices and future opportunities.Human genomics · 2025Review
- A Perspective on Artificial Intelligence for Molecular Pathologists.The Journal of molecular diagnostics : JMD · 2025Review
- Variant effect predictor correlation with functional assays is reflective of clinical classification performance.Genome biology · 2025Article
- Towards a standard benchmark for phenotype-driven variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework.BMC bioinformatics · 2025Article
- Article
- Recent Advances in the Genetics of Ataxias: An Update on Novel Autosomal Dominant Repeat Expansions.Current neurology and neuroscience reports · 2025Review
- Language Modelling Techniques for Analysing the Impact of Human Genetic Variation.Bioinformatics and biology insights · 2025Review
- Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease.Cell reports methods · 2024Article
- Rare disease genomics and precision medicine.Genomics & informatics · 2024Review
- Article
- Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.Human genomics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 2 countries.
Funding
Abstract
Effective computer-aided or automated variant evaluations for monogenic diseases will expedite clinical diagnostic and research efforts of known and novel disease-causing genes. Here we introduce MAVERICK: a Mendelian Approach to Variant Effect pRedICtion built in Keras. MAVERICK is an ensemble of transformer-based neural networks that can classify a wide range of protein-altering single nucleotide variants (SNVs) and indels and assesses whether a variant would be pathogenic in the context of dominant or recessive inheritance. We demonstrate that MAVERICK outperforms all other major programs that assess pathogenicity in a Mendelian context. In a cohort of 644 previously solved patients with Mendelian diseases, MAVERICK ranks the causative pathogenic variant within the top five variants in over 95% of cases. Seventy-six percent of cases were solved by the top-ranked variant. MAVERICK ranks the causative pathogenic variant in hitherto novel disease genes within the first five candidate variants in 70% of cases. MAVERICK has already facilitated the identification of a novel disease gene causing a degenerative motor neuron disease. These results represent a significant step towards automated identification of causal variants in patients with Mendelian diseases.
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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.