pubmed2ensembl
pubmed2ensembl links Ensembl BioMart genomic data with biomedical literature from PubMed and PubMed Central by integrating curated (Entrez Gene) and text-mined (MEDLINE) gene–publication associations across over 2 million PubMed articles and nearly 150,000 genes in 50 species.
Key Features:
- Extensive Database Linking: Connects over 2 million PubMed articles to nearly 150,000 Ensembl genes across 50 species.
- Curated and Automated Data Sources: Integrates curated links from Entrez Gene and automatically generated links from text-mining MEDLINE records.
- Customizable Data Filtering: Allows filtering and combination of multiple gene–publication data sources for targeted analyses.
- Text-based Literature–Genome Querying: Supports queries against PubMed and PubMed Central text combined with constraints on genomic features.
- Automated BioMart Construction Scripting Language: Provides a scripting language to automate construction and customization of BioMarts.
Scientific Applications:
- Literature retrieval for genomic regions: Retrieve publications linked to specific genomic regions or genes for functional interpretation.
- Gene-set literature aggregation: Aggregate and analyze publications associated with functionally related gene sets.
- Cross-species literature mapping: Map literature evidence to orthologous genes across 50 species in Ensembl for comparative studies.
Methodology:
Integrates curated Entrez Gene links and text-mined associations from MEDLINE, maps PubMed/PubMed Central publications to Ensembl gene identifiers across species, and extends Ensembl BioMart with publication links using an automated BioMart construction scripting language.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Perl
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Baran J, Gerner M, Haeussler M, Nenadic G, Bergman CM. pubmed2ensembl: A Resource for Mining the Biological Literature on Genes. PLoS ONE. 2011;6(9):e24716. doi:10.1371/journal.pone.0024716. PMID:21980353. PMCID:PMC3183000.