FuncFetch: an LLM-assisted workflow enables mining thousands of enzyme–substrate interactions from published manuscripts

Authors

Nathaniel Smith (ORCID: https://orcid.org/0009-0004-5672-8081)
Gaurav D. Moghe (ORCID: https://orcid.org/0000-0002-8761-064X)
Xinyu Yuan (ORCID: https://orcid.org/0009-0006-9199-7652)
Chesney Melissinos (ORCID: https://orcid.org/0009-0005-4443-8797)

Institutions

Cornell University (US)

Publication Details

Journal: Bioinformatics
Published: 2024-12-20
DOI: https://doi.org/10.1093/bioinformatics/btae756
Citations: 14
Primary Topic: Microbial Metabolism and Applications
Type: article
Field-Weighted Citation Impact: 5.41

Funders

National Science Foundation

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article

FuncFetch: an LLM-assisted workflow enables mining thousands of enzyme–substrate interactions from published manuscripts

Nathaniel Smith, Gaurav D. Moghe, Xinyu Yuan, Chesney Melissinos

Dec 20, 2024

14 citations

Bioinformatics

Microbial Metabolism and Applications

5.41

article

FuncFetch: an LLM-assisted workflow enables mining thousands of enzyme–substrate interactions from published manuscripts

Nathaniel Smith, Gaurav D. Moghe, Xinyu Yuan, Chesney Melissinos

December 20, 2024article en

14 citations

Abstract

No abstract available for this paper.

BioinformaticsVol. 41(1)

Cornell University (US)

National Science Foundation

Quality Education

Openalex Percentile: Top 4%

Microbial Metabolism and Applications

5.41

DOI Open Access PDF OpenAlex

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FuncFetch: an LLM-assisted workflow enables mining thousands of enzyme–substrate interactions from published manuscripts — Nathaniel Smith, Gaurav D. Moghe, et al. · Bioinformatics (2024) | TGRS Research Map | TGRS