MapperGPT: Large Language Models for Linking and Mapping Entities

1 code implementation • 5 Oct 2023 • Nicolas Matentzoglu, J. Harry Caufield, Harshad B. Hegde, Justin T. Reese, Sierra Moxon, HyeongSik Kim, Nomi L. Harris, Melissa A Haendel, Christopher J. Mungall

Here we present MapperGPT, an approach that uses LLMs to review and refine mapping relationships as a post-processing step, in concert with existing high-recall methods that are based on lexical and structural heuristics.

Anatomy Data Integration +1

Gene Set Summarization using Large Language Models

no code implementations • 21 May 2023 • Marcin P. Joachimiak, J. Harry Caufield, Nomi L. Harris, HyeongSik Kim, Christopher J. Mungall

This is typically done as a statistical enrichment analysis that measures the over- or under-representation of biological function terms associated with genes or their properties, based on curated assertions from a knowledge base (KB) such as the Gene Ontology (GO).

Structured prompt interrogation and recursive extraction of semantics (SPIRES): A method for populating knowledge bases using zero-shot learning

1 code implementation • 5 Apr 2023 • J. Harry Caufield, Harshad Hegde, Vincent Emonet, Nomi L. Harris, Marcin P. Joachimiak, Nicolas Matentzoglu, HyeongSik Kim, Sierra A. T. Moxon, Justin T. Reese, Melissa A. Haendel, Peter N. Robinson, Christopher J. Mungall

Creating knowledge bases and ontologies is a time consuming task that relies on a manual curation.

Relation Extraction Zero-Shot Learning