ArticleBMC bioinformatics2011
Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers.
Article in BMC bioinformatics, 2011. 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.
- BELB: a biomedical entity linking benchmark.Bioinformatics (Oxford, England) · 2023Review
- ResidueFinder: extracting individual residue mentions from protein literature.Journal of biomedical semantics · 2021Article
- Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature.Briefings in bioinformatics · 2021Review
- Building a PubMed knowledge graph.Scientific data · 2020Article
- Exploiting and assessing multi-source data for supervised biomedical named entity recognition.Bioinformatics (Oxford, England) · 2018Article
- The SNPcurator: literature mining of enriched SNP-disease associations.Database : the journal of biological databases and curation · 2018Article
- tmVar 2.0: integrating genomic variant information from literature with dbSNP and ClinVar for precision medicine.Bioinformatics (Oxford, England) · 2018Article
- Two SNPs in the promoter region of Toll-like receptor 4 gene are not associated with smoking in Saudi Arabia.OncoTargets and therapy · 2017Article
- Establishing a baseline for literature mining human genetic variants and their relationships to disease cohorts.BMC medical informatics and decision making · 2016Article
- Computational Analysis of Damaging Single-Nucleotide Polymorphisms and Their Structural and Functional Impact on the Insulin Receptor.BioMed research international · 2016Article
- Article
- Incorporation of personal single nucleotide polymorphism (SNP) data into a national level electronic health record for disease risk assessment, part 1: an overview of requirements.JMIR medical informatics · 2014Article
- Associating disease-related genetic variants in intergenic regions to the genes they impact.PeerJ · 2014Article
- Mutation extraction tools can be combined for robust recognition of genetic variants in the literature.F1000Research · 2014Article
- An analysis on the entity annotations in biological corpora.F1000Research · 2014Review
- The Relationship between ALA16VAL Single Gene Polymorphism and Renal Cell Carcinoma.Advances in urology · 2014Article
- GeneView: a comprehensive semantic search engine for PubMed.Nucleic acids research · 2012Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMost information on genomic variations and their associations with phenotypes are covered exclusively in scientific publications rather than in structured databases. These texts commonly describe variations using natural language; database identifiers are seldom mentioned. This complicates the retrieval of variations, associated articles, as well as information extraction, e. g. the search for biological implications. To overcome these challenges, procedures to map textual mentions of variations to database identifiers need to be developed.
resultsThis article describes a workflow for normalization of variation mentions, i.e. the association of them to unique database identifiers. Common pitfalls in the interpretation of single nucleotide polymorphism (SNP) mentions are highlighted and discussed. The developed normalization procedure achieves a precision of 98.1 % and a recall of 67.5% for unambiguous association of variation mentions with dbSNP identifiers on a text corpus based on 296 MEDLINE abstracts containing 527 mentions of SNPs. The annotated corpus is freely available at http://www.scai.fraunhofer.de/snp-normalization-corpus.html.
conclusionsComparable approaches usually focus on variations mentioned on the protein sequence and neglect problems for other SNP mentions. The results presented here indicate that normalizing SNPs described on DNA level is more difficult than the normalization of SNPs described on protein level. The challenges associated with normalization are exemplified with ambiguities and errors, which occur in this corpus.
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