Bioinformatics Copilot 2.0 for Transcriptomic Data Analysis
Wang, Y.; Zhang, W.; Wong, I.; Lin, S.; Kumar, R.; Wang, A.
Show 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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