ArticleJournal of the American Medical Informatics Association : JAMIA
A literature search tool for intelligent extraction of disease-associated genes.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- Article
- Analyzing a co-occurrence gene-interaction network to identify disease-gene association.BMC bioinformatics · 2019Article
- Cross-disorder comparative analysis of comorbid conditions reveals novel autism candidate genes.BMC genomics · 2017Article
- Comorbid Analysis of Genes Associated with Autism Spectrum Disorders Reveals Differential Evolutionary Constraints.PloS one · 2016Article
- Translational Meta-analytical Methods to Localize the Regulatory Patterns of Neurological Disorders in the Human Brain.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015Article
- FLAGS, frequently mutated genes in public exomes.BMC medical genomics · 2014Article
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
objectiveTo extract disorder-associated genes from the scientific literature in PubMed with greater sensitivity for literature-based support than existing methods.
methodsWe developed a PubMed query to retrieve disorder-related, original research articles. Then we applied a rule-based text-mining algorithm with keyword matching to extract target disorders, genes with significant results, and the type of study described by the article.
resultsWe compared our resulting candidate disorder genes and supporting references with existing databases. We demonstrated that our candidate gene set covers nearly all genes in manually curated databases, and that the references supporting the disorder-gene link are more extensive and accurate than other general purpose gene-to-disorder association databases.
conclusionsWe implemented a novel publication search tool to find target articles, specifically focused on links between disorders and genotypes. Through comparison against gold-standard manually updated gene-disorder databases and comparison with automated databases of similar functionality we show that our tool can search through the entirety of PubMed to extract the main gene findings for human diseases rapidly and accurately.
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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.