Due to the sheer volume of the medical literature and high cost of expert curation, curated variant information in existing databases is found to be incomplete and out of date [1]. In addition, variants are often asserted with different names (e.g., V600E vs. T1799A) in publications thus a search in PubMed using only one name usually cannot retrieve all relevant articles. Hence, to help scientists, healthcare professionals, and database curators keep up-to-date with newly published research, we have developed LitVar [2], a novel web-based tool that combines robust and advanced text mining with data integrations from PubMed, dbSNP, and ClinVar for accurate search of variants and related gene, disease and drug information.

• [1] Wei, C.H., Phan, L., Feltz, J., Maiti, R., Hefferon, T. and Lu, Z. (2017) tmVar 2.0: Integrating genomic variant information from literature with dbSNP and ClinVar for precision medicine. Bioinformatics.
• [2] Allot, A., Peng, Y., Wei, C.H., Lee, K., Phan, L. and Lu, Z. (2018) LitVar: a semantic search engine for linking genomic variant data in PubMed and PMC. Nucleic Acids Res.

LitVar is developed by the NCBI Text Mining Research Group at the Computational Biology Branch, with help from the dbSNP group at the Information Engineering Branch. We invite your feedback – please send your comments and suggestions to:

• Alexis Allot
• Yifan Peng
• Zhiyong Lu

This research is supported by the Intramural Research Programs of the National Institutes of Health, National Library of Medicine.