ArticleDatabase : the journal of biological databases and curation2015
PhenoMiner: from text to a database of phenotypes associated with OMIM diseases.
Article in Database : the journal of biological databases and curation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Network Pharmacology Combined with Experimental Validation to Investigate the Effects and Mechanisms of Aucubin on Aging-Related Muscle Atrophy.International journal of molecular sciences · 2025Article
- PheSom: a term frequency-based method for measuring human phenotype similarity on the basis of MeSH vocabulary.Frontiers in genetics · 2023Article
- Creation and evaluation of full-text literature-derived, feature-weighted disease models of genetically determined developmental disorders.Database : the journal of biological databases and curation · 2022Article
- Recent advances in biomedical literature mining.Briefings in bioinformatics · 2021Review
- DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.PLoS computational biology · 2020Article
- AMELIE speeds Mendelian diagnosis by matching patient phenotype and genotype to primary literature.Science translational medicine · 2020Article
- Applying citizen science to gene, drug and disease relationship extraction from biomedical abstracts.Bioinformatics (Oxford, England) · 2020Article
- Annotating and detecting phenotypic information for chronic obstructive pulmonary disease.JAMIA open · 2019Article
- Genetics of Human Primary Hypertension: Focus on Hormonal Mechanisms.Endocrine reviews · 2019Review
- The utility of phenomics in diagnosis of inherited metabolic disorders.Clinical medicine (London, England) · 2019Review
- Automated Methods Enable Direct Computation on Phenotypic Descriptions for Novel Candidate Gene Prediction.Frontiers in plant science · 2019Article
- TiSAn: estimating tissue-specific effects of coding and non-coding variants.Bioinformatics (Oxford, England) · 2018Article
- A gene-phenotype relationship extraction pipeline from the biomedical literature using a representation learning approach.Bioinformatics (Oxford, England) · 2018Article
- Phenotype Instance Verification and Evaluation Tool (PIVET): A Scaled Phenotype Evidence Generation Framework Using Web-Based Medical Literature.Journal of medical Internet research · 2018Article
- A new synonym-substitution method to enrich the human phenotype ontology.BMC bioinformatics · 2017Article
- NiaoDuQing granules relieve chronic kidney disease symptoms by decreasing renal fibrosis and anemia.Oncotarget · 2017Article
- Novel bioinformatic developments for exome sequencing.Human genetics · 2016Review
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Authors and funding
6 authors.
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Abstract
Analysis of scientific and clinical phenotypes reported in the experimental literature has been curated manually to build high-quality databases such as the Online Mendelian Inheritance in Man (OMIM). However, the identification and harmonization of phenotype descriptions struggles with the diversity of human expressivity. We introduce a novel automated extraction approach called PhenoMiner that exploits full parsing and conceptual analysis. Apriori association mining is then used to identify relationships to human diseases. We applied PhenoMiner to the BMC open access collection and identified 13,636 phenotype candidates. We identified 28,155 phenotype-disorder hypotheses covering 4898 phenotypes and 1659 Mendelian disorders. Analysis showed: (i) the semantic distribution of the extracted terms against linked ontologies; (ii) a comparison of term overlap with the Human Phenotype Ontology (HP); (iii) moderate support for phenotype-disorder pairs in both OMIM and the literature; (iv) strong associations of phenotype-disorder pairs to known disease-genes pairs using PhenoDigm. The full list of PhenoMiner phenotypes (S1), phenotype-disorder associations (S2), association-filtered linked data (S3) and user database documentation (S5) is available as supplementary data and can be downloaded at http://github.com/nhcollier/PhenoMiner under a Creative Commons Attribution 4.0 license. Database URL: phenominer.mml.cam.ac.uk.
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