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bioRxiv · 10.1101/2024.08.15.607673

Bioinformatics Copilot 2.0 for Transcriptomic Data Analysis

Wang, Y.·Zhang, W.·Wong, I.·Lin, S.·Kumar, R.·Wang, A.
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Abstract

Large language models, when integrated into bioinformatics tools, offer valuable support for biologists in the analysis of single-cell transcriptomic data. Here, we introduce Bioinformatics Copilot 2.0, an advanced tool that builds upon its predecessor with four significant enhancements: 1) Internal server processing: users can now process large datasets on an internal server, thereby ensuring data privacy. 2) User-controlled analysis: users can take control of their data analysis when tasks exceed the copilots capabilities.3) Real-time information access: users can access up-to-date information from online resources, such as gene function queries and recent publications, thus enhancing data interpretation. 4) Data analysis and result documentation: the copilot now supports the generation of PDFs that include images and detailed analysis. These advancements represent a step towards building a bioinformatics autopilot. Demonstration videos showcasing these features are available at www.biochemml.com/tools.

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Wang, Y., Zhang, W., Wong, I., Lin, S., Kumar, R., Wang, A.. 2024-08-19. Bioinformatics Copilot 2.0 for Transcriptomic Data Analysis. https://doi.org/10.1101/2024.08.15.607673

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