INDRA BERT Variant NER

Extract variant mentions from biomedical text with INDRA BERT models.

Choose a model from the gyorilab/indra-bert collection, pick a Hub revision, and test how each checkpoint tags proteins, DNA variants, rsIDs, and copy-number spans.

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Exemplar text

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Input text

In our cohort we analyzed variants affecting neuronal signaling and cytoskeletal stability. Sequencing identified several recurrent protein mutations including TP53 R248W, EGFR L858R, and a truncating MAPT Q336* variant predicted to disrupt microtubule binding. At the DNA level we detected substitutions such as TP53 c.743G>A and EGFR c.2573T>G, along with a small deletion c.152_153del causing a frameshift in downstream transcripts. Structural variation analysis further revealed a copy number gain consistent with chr7:55,019,017-55,242,524, overlapping the EGFR locus and resembling CNV strings commonly reported in PubTator3-style annotations. Population-associated polymorphisms were also present, including rs429358 and rs7412 within APOE, as well as rs1801133 in MTHFR. Together, these protein-altering mutations, nucleotide substitutions, and regional copy number changes suggest combined effects on cellular stress responses, signaling pathways, and metabolic regulation in the studied samples.

Python pipeline example

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Predicted entities

Predicted entities