ArticleScientific reports2025
The influence of prompt engineering on large language models for protein-protein interaction identification in biomedical literature.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Multimodal knowledge expansion widget powered by plant protein phosphorylation database and ChatGPT.Frontiers in bioinformatics · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Identifying protein-protein interactions (PPIs) is a foundational task in biomedical natural language processing. While specialized models have been developed, the potential of general-domain large language models (LLMs) in PPI extraction, particularly for researchers without computational expertise, remains unexplored. This study evaluates the effectiveness of proprietary LLMs (GPT-3.5, GPT-4, and Google Gemini) in PPI prediction through systematic prompt engineering. We designed six prompting scenarios of increasing complexity, from basic interaction queries to sophisticated entity-tagged formats, and assessed model performance across multiple benchmark datasets (LLL, IEPA, HPRD50, AIMed, BioInfer, and PEDD). Carefully designed prompts effectively guided LLMs in PPI prediction. Gemini 1.5 Pro achieved the highest performance across most datasets, with notable F
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.