ExTRI (Rbbt)

Extraction of information on transcription factors and their targets from the literature.

Institution:

Institution

Research Group:

BSC Group: Life Sciences

Researcher/s:

Miguel Vazquez

Description:

ExTRI applies natural-language processing to extract transcription-factor–target interactions from PubMed and other corpora, populating a machine-readable regulatory network that downstream analytics can query. This directly supports the trend of feeding AI pipelines with FAIR, up-to-date biomedical knowledge.

ExTRI is a literature-mining engine that feeds data-driven decision pipelines by auto-curating TF–target networks. GPU-enabled NLP, containerised workflows and large-scale accuracy benchmarking will be key for industrial adoption by pharma knowledge-engineering and precision-omics teams.

Value Proposition:

Spin up a real-time literature-network knowledge-graph

Aplication areas:

Drug discovery, drug development, biomarker discovery, omics sciences

Target market:

Pharmaceutical; IVD diagnostics

Protection:

MIT License

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