ArticlePloS one2012
SR4GN: a species recognition software tool for gene normalization.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
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- Named Entity Recognition and Normalization for Alzheimer's Disease Eligibility Criteria.Proceedings. IEEE International Conference on Healthcare Informatics · 2023Article
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- PlagueKD: a knowledge graph-based plague knowledge database.Database : the journal of biological databases and curation · 2022Article
- Expanding a database-derived biomedical knowledge graph via multi-relation extraction from biomedical abstracts.BioData mining · 2022Article
- Assigning species information to corresponding genes by a sequence labeling framework.Database : the journal of biological databases and curation · 2022Article
- PHILM2Web: A high-throughput database of macromolecular host-pathogen interactions on the Web.Database : the journal of biological databases and curation · 2022Article
- RegEl corpus: identifying DNA regulatory elements in the scientific literature.Database : the journal of biological databases and curation · 2022Article
- Plant phenotype relationship corpus for biomedical relationships between plants and phenotypes.Scientific data · 2022Article
- HerbKG: Constructing a Herbal-Molecular Medicine Knowledge Graph Using a Two-Stage Framework Based on Deep Transfer Learning.Frontiers in genetics · 2022Article
- Taxallnomy: an extension of NCBI Taxonomy that produces a hierarchically complete taxonomic tree.BMC bioinformatics · 2021Article
- NLM-Gene, a richly annotated gold standard dataset for gene entities that addresses ambiguity and multi-species gene recognition.Journal of biomedical informatics · 2021Article
- Building a PubMed knowledge graph.Scientific data · 2020Article
- BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale.PLoS computational biology · 2020Article
- Named Entity Recognition and Relation Detection for Biomedical Information Extraction.Frontiers in cell and developmental biology · 2020Review
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3 authors.
Funding
Abstract
As suggested in recent studies, species recognition and disambiguation is one of the most critical and challenging steps in many downstream text-mining applications such as the gene normalization task and protein-protein interaction extraction. We report SR4GN: an open source tool for species recognition and disambiguation in biomedical text. In addition to the species detection function in existing tools, SR4GN is optimized for the Gene Normalization task. As such it is developed to link detected species with corresponding gene mentions in a document. SR4GN achieves 85.42% in accuracy and compares favorably to the other state-of-the-art techniques in benchmark experiments. Finally, SR4GN is implemented as a standalone software tool, thus making it convenient and robust for use in many text-mining applications. SR4GN can be downloaded at: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/downloads/SR4GN.
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