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Automating literature discovery and synthesis allows researchers to manage the increasing volume of scientific publications with significantly greater efficiency. This training provides a practical framework for building a custom AI research assistant using R and professional literature APIs to systematically identify papers on specific topics, such as the relationship between TP53 and cancer. Participants will learn how to visualize these search results and utilize Large Language Models (LLMs) to synthesize complex information into a structured research blog. By the end of the course, you will have a reproducible, R-based workflow that transforms raw literature searches into accessible, AI-generated summaries.
Learning outcomes: AI | Access literature databases via an API | Large Language Models | Text Mining | Data Visualisation
Prerequisites: Basic knowledge of R programming
Automating literature discovery and synthesis allows researchers to manage the increasing volume of scientific publications with significantly greater efficiency. This training provides a practical framework for building a custom AI research assistant using R and professional literature APIs to systematically identify papers on specific topics, such as the relationship between TP53 and cancer. Participants will learn how to visualize these search results and utilize Large Language Models (LLMs) to synthesize complex information into a structured research blog. By the end of the course, you will have a reproducible, R-based workflow that transforms raw literature searches into accessible, AI-generated summaries.
Learning outcomes: AI | Access literature databases via an API | Large Language Models | Text Mining | Data Visualisation
Prerequisites: Basic knowledge of R programming