ArticleBioinformatics (Oxford, England)2011
Annotating genes and genomes with DNA sequences extracted from biomedical articles.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Interactive tools for functional annotation of bacterial genomes.Database : the journal of biological databases and curation · 2024Article
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- Strategies for Enriching Variant Coverage in Candidate Disease Loci on a Multiethnic Genotyping Array.PloS one · 2016Article
- The UCSC Genome Browser database: 2015 update.Nucleic acids research · 2015Article
- Mining locus tags in PubMed Central to improve microbial gene annotation.BMC bioinformatics · 2014Article
- The UCSC Genome Browser database: 2014 update.Nucleic acids research · 2014Article
- Evaluating gold standard corpora against gene/protein tagging solutions and lexical resources.Journal of biomedical semantics · 2013Article
- Database citation in full text biomedical articles.PloS one · 2013Article
- The UCSC Genome Browser database: extensions and updates 2013.Nucleic acids research · 2013Article
- Improving links between literature and biological data with text mining: a case study with GEO, PDB and MEDLINE.Database : the journal of biological databases and curation · 2012Article
- Extraction of data deposition statements from the literature: a method for automatically tracking research results.Bioinformatics (Oxford, England) · 2011Article
- Translational web robots for pathogen genome analysis.Microbial informatics and experimentation · 2011Article
- The GNAT library for local and remote gene mention normalization.Bioinformatics (Oxford, England) · 2011Article
- Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
motivationIncreasing rates of publication and DNA sequencing make the problem of finding relevant articles for a particular gene or genomic region more challenging than ever. Existing text-mining approaches focus on finding gene names or identifiers in English text. These are often not unique and do not identify the exact genomic location of a study.
resultsHere, we report the results of a novel text-mining approach that extracts DNA sequences from biomedical articles and automatically maps them to genomic databases. We find that ∼20% of open access articles in PubMed central (PMC) have extractable DNA sequences that can be accurately mapped to the correct gene (91%) and genome (96%). We illustrate the utility of data extracted by text2genome from more than 150 000 PMC articles for the interpretation of ChIP-seq data and the design of quantitative reverse transcriptase (RT)-PCR experiments.
conclusionOur approach links articles to genes and organisms without relying on gene names or identifiers. It also produces genome annotation tracks of the biomedical literature, thereby allowing researchers to use the power of modern genome browsers to access and analyze publications in the context of genomic data. AVAILABILITY AND IMPLEMENTATION: Source code is available under a BSD license from http://sourceforge.net/projects/text2genome/ and results can be browsed and downloaded at http://text2genome.org.
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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.