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Table 1 Literature mining approaches for mutation extraction. The additional materials sections (Additional file 1) provides a more detailed description of each method.

From: Extraction of human kinase mutations from literature, databases and genotyping studies

Collection of existing mutation extraction approaches
Method Main characteristics and descriptive keywords of the approach Ref
MEMA Uses regular expressions, gene and protein mention detection, co-mention proximity, OMIM validation [19]
MuteXt Uses regular expressions, GPCR and NR mention detection, co-mention proximity, sequence check [27]
Yip et al. Uses regular expressions, protein mention detection, SwissProt validation, extensive sequence check [28]
CoagMDB Uses regular expressions, serine protease mention detection, sequence check [41]
Mutation GraB Uses regular expressions, protein mention detection, graph shorted distance, sequence check [20]
Mutation Miner Uses regular expressions, protein mention detection, sentence co-mention [21]
MuGeX Uses regular expressions, protein mention detection, protein and DNA mutation disambiguation [24]
VTag Machine learning (CRF) detection of acquired sequence variations mentions (mutations, translocations, deletions) [26]
OSIRISv1.2 Detection of human gene variations corresponding to SNPs [42]
MutationFinder Uses regular expressions and patterns, protein mutations, complex language expressions [23]