ArticleBioinformatics (Oxford, England)2012
Bayesian ontology querying for accurate and noise-tolerant semantic searches.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed.
- 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
- 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
- A Phenotypic Paradigm for Cerebral Palsy Genetics.medRxiv : the preprint server for health sciences · 2026Article
- First steps toward building natural history of diseases computationally: Lessons learned from the Noonan syndrome use case.American journal of human genetics · 2025Article
- A phenotype-based AI pipeline outperforms human experts in differentially diagnosing rare diseases using EHRs.NPJ digital medicine · 2025Article
- Pheno-Ranker: a toolkit for comparison of phenotypic data stored in GA4GH standards and beyond.BMC bioinformatics · 2024Article
- Objectivizing issues in the diagnosis of complex rare diseases: lessons learned from testing existing diagnosis support systems on ciliopathies.BMC medical informatics and decision making · 2024Article
- Enhancing Variant Prioritization in VarFish through On-Premise Computational Facial Analysis.Genes · 2024Article
- Phenotypic similarity-based approach for variant prioritization for unsolved rare disease: a preliminary methodological report.European journal of human genetics : EJHG · 2024Article
- IMPatienT: An Integrated Web Application to Digitize, Process and Explore Multimodal PATIENt daTa.Journal of neuromuscular diseases · 2024Article
- Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology.American journal of medical genetics. Part C, Seminars in medical genetics · 2022Article
- Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes.Frontiers in genetics · 2021Review
- The case for open science: rare diseases.JAMIA open · 2020Review
- Diagnosis support systems for rare diseases: a scoping review.Orphanet journal of rare diseases · 2020Article
- Article
- Incremental data integration for tracking genotype-disease associations.PLoS computational biology · 2020Article
- PEDIA: prioritization of exome data by image analysis.Genetics in medicine : official journal of the American College of Medical Genetics · 2019Article
- Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics.Current protocols in human genetics · 2019Article
- ClinPhen extracts and prioritizes patient phenotypes directly from medical records to expedite genetic disease diagnosis.Genetics in medicine : official journal of the American College of Medical Genetics · 2019Article
- Rapid and accurate interpretation of clinical exomes using Phenoxome: a computational phenotype-driven approach.European journal of human genetics : EJHG · 2019Article
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.
Funding
Abstract
motivationOntologies provide a structured representation of the concepts of a domain of knowledge as well as the relations between them. Attribute ontologies are used to describe the characteristics of the items of a domain, such as the functions of proteins or the signs and symptoms of disease, which opens the possibility of searching a database of items for the best match to a list of observed or desired attributes. However, naive search methods do not perform well on realistic data because of noise in the data, imprecision in typical queries and because individual items may not display all attributes of the category they belong to.
resultsWe present a method for combining ontological analysis with Bayesian networks to deal with noise, imprecision and attribute frequencies and demonstrate an application of our method as a differential diagnostic support system for human genetics. AVAILABILITY: We provide an implementation for the algorithm and the benchmark at http://compbio.charite.de/boqa/. CONTACT: Sebastian.Bauer@charite.de or Peter.Robinson@charite.de SUPPLEMENTARY INFORMATION: Supplementary Material for this article is available at Bioinformatics online.
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.