ArticleBMC bioinformatics2009
Annotation of protein residues based on a literature analysis: cross-validation against UniProtKb.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 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
- Automatic annotation of protein residues in published papers.Acta crystallographica. Section F, Structural biology communications · 2019Article
- A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- nala: text mining natural language mutation mentions.Bioinformatics (Oxford, England) · 2017Article
- Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.Briefings in bioinformatics · 2017Article
- Establishing a baseline for literature mining human genetic variants and their relationships to disease cohorts.BMC medical informatics and decision making · 2016Article
- Literature mining of genetic variants for curation: quantifying the importance of supplementary material.Database : the journal of biological databases and curation · 2014Article
- An analysis on the entity annotations in biological corpora.F1000Research · 2014Review
- Mutation extraction tools can be combined for robust recognition of genetic variants in the literature.F1000Research · 2014Article
- Approximate subgraph matching-based literature mining for biomedical events and relations.PloS one · 2013Article
- Detection of protein catalytic sites in the biomedical literature.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2013Article
- Text-mining solutions for biomedical research: enabling integrative biology.Nature reviews. Genetics · 2012Review
- The curation of genetic variants: difficulties and possible solutions.Genomics, proteomics & bioinformatics · 2012Review
- Multiple graph regularized protein domain ranking.BMC bioinformatics · 2012Article
- Literature mining of protein-residue associations with graph rules learned through distant supervision.Journal of biomedical semantics · 2012Article
- Getting personalized cancer genome analysis into the clinic: the challenges in bioinformatics.Genome medicine · 2012Review
- Text mining improves prediction of protein functional sites.PloS one · 2012Article
- Between proteins and phenotypes: annotation and interpretation of mutations.BMC bioinformatics · 2009Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA protein annotation database, such as the Universal Protein Resource knowledge base (UniProtKb), is a valuable resource for the validation and interpretation of predicted 3D structure patterns in proteins. Existing studies have focussed on point mutation extraction methods from biomedical literature which can be used to support the time consuming work of manual database curation. However, these methods were limited to point mutation extraction and do not extract features for the annotation of proteins at the residue level.
resultsThis work introduces a system that identifies protein residues in MEDLINE abstracts and annotates them with features extracted from the context written in the surrounding text. MEDLINE abstract texts have been processed to identify protein mentions in combination with taxonomic species and protein residues (F1-measure 0.52). The identified protein-species-residue triplets have been validated and benchmarked against reference data resources (UniProtKb, average F1-measure of 0.54). Then, contextual features were extracted through shallow and deep parsing and the features have been classified into predefined categories (F1-measure ranges from 0.15 to 0.67). Furthermore, the feature sets have been aligned with annotation types in UniProtKb to assess the relevance of the annotations for ongoing curation projects. Altogether, the annotations have been assessed automatically and manually against reference data resources.
conclusionThis work proposes a solution for the automatic extraction of functional annotation for protein residues from biomedical articles. The presented approach is an extension to other existing systems in that a wider range of residue entities are considered and that features of residues are extracted as annotations.
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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.