ArticleBMC genomics2010
Algorithms and semantic infrastructure for mutation impact extraction and grounding.
Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- 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
- tmVar 2.0: integrating genomic variant information from literature with dbSNP and ClinVar for precision medicine.Bioinformatics (Oxford, England) · 2018Article
- A semantic-based workflow for biomedical literature annotation.Database : the journal of biological databases and curation · 2017Article
- Text Mining Genotype-Phenotype Relationships from Biomedical Literature for Database Curation and Precision Medicine.PLoS computational biology · 2016Article
- Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- A Semantic Web-based System for Mining Genetic Mutations in Cancer Clinical Trials.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- The HIV mutation browser: a resource for human immunodeficiency virus mutagenesis and polymorphism data.PLoS computational biology · 2014Article
- Benchmarking infrastructure for mutation text mining.Journal of biomedical semantics · 2014Article
- Towards precision medicine: advances in computational approaches for the analysis of human variants.Journal of molecular biology · 2013Review
- A novel knowledge representation framework for the statistical validation of quantitative imaging biomarkers.Journal of digital imaging · 2013Review
- Chapter 15: disease gene prioritization.PLoS computational biology · 2013Article
- Annotating the biomedical literature for the human variome.Database : the journal of biological databases and curation · 2013Article
- Semantically enabling a genome-wide association study database.Journal of biomedical semantics · 2012Article
- Bioinformatics for personal genome interpretation.Briefings in bioinformatics · 2012Review
- Mining the pharmacogenomics literature--a survey of the state of the art.Briefings in bioinformatics · 2012Article
- Automated extraction and semantic analysis of mutation impacts from the biomedical literature.BMC genomics · 2012Article
- Towards linked open gene mutations data.BMC bioinformatics · 2012Article
- Text mining improves prediction of protein functional sites.PloS one · 2012Article
- Semantically enabling pharmacogenomic data for the realization of personalized medicine.Pharmacogenomics · 2012Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMutation impact extraction is a hitherto unaccomplished task in state of the art mutation extraction systems. Protein mutations and their impacts on protein properties are hidden in scientific literature, making them poorly accessible for protein engineers and inaccessible for phenotype-prediction systems that currently depend on manually curated genomic variation databases.
resultsWe present the first rule-based approach for the extraction of mutation impacts on protein properties, categorizing their directionality as positive, negative or neutral. Furthermore protein and mutation mentions are grounded to their respective UniProtKB IDs and selected protein properties, namely protein functions to concepts found in the Gene Ontology. The extracted entities are populated to an OWL-DL Mutation Impact ontology facilitating complex querying for mutation impacts using SPARQL. We illustrate retrieval of proteins and mutant sequences for a given direction of impact on specific protein properties. Moreover we provide programmatic access to the data through semantic web services using the SADI (Semantic Automated Discovery and Integration) framework.
conclusionWe address the problem of access to legacy mutation data in unstructured form through the creation of novel mutation impact extraction methods which are evaluated on a corpus of full-text articles on haloalkane dehalogenases, tagged by domain experts. Our approaches show state of the art levels of precision and recall for Mutation Grounding and respectable level of precision but lower recall for the task of Mutant-Impact relation extraction. The system is deployed using text mining and semantic web technologies with the goal of publishing to a broad spectrum of consumers.
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