ReviewGenome medicine2015
Phenotype-driven strategies for exome prioritization of human Mendelian disease genes.
Review in Genome medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.
What it found
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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
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
79 citing papers in PubMed.
- IFIH1 loss-of-function variants contribute to very early-onset inflammatory bowel disease.Human genetics · 2021Trial
- PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Multimodal integrated knowledge transfer to large language models through preference optimization with biomedical applications.Patterns (New York, N.Y.) · 2026Article
- RankVar: machine learning-based variant ranking and reinterpretation for rare genetic diseases.Genome medicine · 2026Article
- G.AI: an AI-driven platform for phenotype standardization, variant interpretation and structured clinical reporting in rare disease genomic diagnosis.Journal of translational medicine · 2026Article
- PhenoSS: Phenotype semantic similarity-based approach for rare disease prediction and patient clustering.medRxiv : the preprint server for health sciences · 2026Article
- Systematic benchmarking demonstrates large language models have not reached the diagnostic accuracy of traditional rare-disease decision support tools.European journal of human genetics : EJHG · 2026Article
- Phenotype-first patient matching with SimPheny identifies diagnostic candidates beyond curated gene associations.medRxiv : the preprint server for health sciences · 2026Article
- An optimized variant prioritization process for rare disease diagnostics: recommendations for Exomiser and Genomiser.Genome medicine · 2025Article
- A Hypergraph powered approach to Phenotype-driven Gene Prioritization and Rare Disease Prediction.Scientific reports · 2025Article
- PhenoDP: leveraging deep learning for phenotype-based case reporting, disease ranking, and symptom recommendation.Genome medicine · 2025Article
- Leveraging clinical intuition to improve accuracy of phenotype-driven prioritization.Genetics in medicine : official journal of the American College of Medical Genetics · 2025Article
- Article
- Prioritization of oligogenic variant combinations in whole exomes.Bioinformatics (Oxford, England) · 2024Article
- Refined preferences of prioritizers improve intelligent diagnosis for Mendelian diseases.Scientific reports · 2024Article
- Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT.Patterns (New York, N.Y.) · 2024Article
- MSeqDR Quick-Mitome (QM): Combining Phenotype-Guided Variant Interpretation and Machine Learning Classifiers to Aid Primary Mitochondrial Disease Genetic Diagnosis.Current protocols · 2024Article
- Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT.ArXiv · 2023Article
- Simulation of undiagnosed patients with novel genetic conditions.Nature communications · 2023Article
- PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework.Nature genetics · 2023Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Whole exome sequencing has altered the way in which rare diseases are diagnosed and disease genes identified. Hundreds of novel disease-associated genes have been characterized by whole exome sequencing in the past five years, yet the identification of disease-causing mutations is often challenging because of the large number of rare variants that are being revealed. Gene prioritization aims to rank the most probable candidate genes towards the top of a list of potentially pathogenic variants. A promising new approach involves the computational comparison of the phenotypic abnormalities of the individual being investigated with those previously associated with human diseases or genetically modified model organisms. In this review, we compare and contrast the strengths and weaknesses of current phenotype-driven computational algorithms, including Phevor, Phen-Gen, eXtasy and two algorithms developed by our groups called PhenIX and Exomiser. Computational phenotype analysis can substantially improve the performance of exome analysis pipelines.
Identifiers
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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.