tmVar 3.0: an improved variant concept recognition and normalization tool
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Abstract (arXiv)
Previous studies have shown that automated text-mining tools are becoming increasingly important for successfully unlocking variant information in scientific literature at large scale. Despite multiple attempts in the past, existing tools are still of limited recognition scope and precision. We propose tmVar 3.0: an improved variant recognition and normalization tool. Compared to its predecessors, tmVar 3.0 is able to recognize a wide spectrum of variant related entities (e.g., allele and copy number variants), and to group different variant mentions belonging to the same concept in an article for improved accuracy. Moreover, tmVar3 provides additional variant normalization options such as allele-specific identifiers from the ClinGen Allele Registry. tmVar3 exhibits a state-of-the-art performance with over 90% accuracy in F-measure in variant recognition and normalization, when evaluated on three independent benchmarking datasets. tmVar3 is freely available for download. We have also processed the entire PubMed and PMC with tmVar3 and released its annotations on our FTP. Availability: ftp://ftp.ncbi.nlm.nih.gov/pub/lu/tmVar3
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 2 of its 15 references that are in the map. First posted on arXiv 7 Apr 2022.
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2 of 15 references.
References · 2
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Citing papers per year: 2022: 2; 2023: 3; 2024: 2; 2025: 1; 2026: 2.
10 papers.
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- 2022AIONER: All-in-one scheme-based biomedical named entity recognition using deep learningcited by 13
- 2024HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization toolscited by 8
- 2023BELB: a Biomedical Entity Linking Benchmarkcited by 7
- 2023EasyNER: A Customizable Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical and Life Science Textcited by 0
- 2025Effective Multi-Task Learning for Biomedical Named Entity Recognitioncited by 0
- 2026Fine-Tuning Models for Biomedical Relation Extractioncited by 0
- 2026BELXTR: Biomedical Entity Linking via Contextualized Token Retrievalcited by 0
- 2026BELXTR: Biomedical Entity Linking via Contextualized Token Retrieval22 Sep 2026
- 2026Fine-Tuning Models for Biomedical Relation Extraction23 Jul 2026
- 2025Effective Multi-Task Learning for Biomedical Named Entity Recognition24 Jul 2025
- 2024HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools19 Feb 2024
- 2024PubTator 3.0: an AI-powered Literature Resource for Unlocking Biomedical Knowledge19 Jan 2024
- 2023BELB: a Biomedical Entity Linking Benchmark22 Aug 2023
- 2023SciMON: Scientific Inspiration Machines Optimized for Novelty23 May 2023
- 2023EasyNER: A Customizable Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical and Life Science Text16 Apr 2023
- 2022AIONER: All-in-one scheme-based biomedical named entity recognition using deep learning30 Nov 2022
- 2022BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing30 Jun 2022