Transforming Pathogen Data Network Resources to RDF using Large Language Models

Automating sequence identification and contextualization using BLAST, database queries, and LLM narrative synthesis to accelerate pathogen and AMR gene discovery

Automated extraction of viral sequence features, mutations, and epitopes from PubMed literature using LLMs to accelerate outbreak response and genomic analysis

Optimizing protein language model to predict viral protein structures at scale

Creating structured question-answer training datasets from BRC resources and publications to train LLMs for bioinformatics workflow generation

Enabling bench scientists to start with analysis goals and receive both relevant datasets and executable workflows—a complete path from question to execution.

Extending the Co-Scientist framework to build reasoning agents for protein function prediction using CEPI and BV-BRC datasets for priority pathogens

Leveraging high-performance retrieval-augmented generation to extract and curate structured biological data for CEPI priority pathogens from scientific literature

Extending the Rhea platform with MCP+RAG to enable automated workflow generation leveraging Galaxy and BV-BRC for infectious disease analysis