Bioinformatics Illustrations Decoded by ChatGPT: The Good, The Bad, and The Ugly Article Swipe

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Jinge Wang , Qing Ye , Li Liu , Nancy Lan Guo , Gangqing Hu ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.1101/2023.10.15.562423

Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting fundamental bioinformatics data analyses. The recent feature of accepting image-inputs by ChatGPT motivated us to explore its efficacy in deciphering bioinformatics illustrations. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when quantitative analysis of visual elements was involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.

Related Topics

Computer Science

Plot (Graphics)

Data Science

Artificial Intelligence

Biology

Biochemistry

Reverse Transcription Polymerase Chain Reaction

Concepts

Proofreading Computer science Plot (graphics) Feature (linguistics) Reliability (semiconductor) Data science Artificial intelligence Natural language processing Linguistics Biology Power (physics) Biochemistry Polymerase Physics Philosophy Gene Statistics Quantum mechanics Mathematics

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Type: preprint
Language: en
Landing Page: https://doi.org/10.1101/2023.10.15.562423
PDF: https://www.biorxiv.org/content/biorxiv/early/2023/10/17/2023.10.15.562423.full.pdf
OA Status: green
Cited By: 5
References: 41
Related Works: 10
OpenAlex ID: https://openalex.org/W4387696533

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OpenAlex ID: https://openalex.org/W4387696533

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DOI: https://doi.org/10.1101/2023.10.15.562423

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Title: Bioinformatics Illustrations Decoded by ChatGPT: The Good, The Bad, and The Ugly

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Type: preprint

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Language: en

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Publication year: 2023

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Publication date: 2023-10-17

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Authors: Jinge Wang, Qing Ye, Li Liu, Nancy Lan Guo, Gangqing Hu

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Landing page: https://doi.org/10.1101/2023.10.15.562423

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PDF URL: https://www.biorxiv.org/content/biorxiv/early/2023/10/17/2023.10.15.562423.full.pdf

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Concepts: Proofreading, Computer science, Plot (graphics), Feature (linguistics), Reliability (semiconductor), Data science, Artificial intelligence, Natural language processing, Linguistics, Biology, Power (physics), Biochemistry, Polymerase, Physics, Philosophy, Gene, Statistics, Quantum mechanics, Mathematics

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Cited by: 5

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Related works (count): 10

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