Knowledge Graphs in Biology

Kim discusses the innovative use of knowledge graphs to enhance biological research, emphasizing how machine learning algorithms can efficiently represent and leverage structured knowledge. By mining historical data and integrating findings from past experiments, researchers can uncover valuable insights and hypotheses about proteins and their interactions, transforming the way scientific literature is accessed and utilized.

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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Machine Learning at GSK with Kim Branson - #536
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- I'm thinking that classical or deep ML solutions have a flaw in that they cannot be extended. For example, if one builds a model and wants to introduce a new feature, typically the model has to be retrained from scratch. So, I'm considering building a Knowledge Graph using LLMs. This knowledge graph would have to include time-dependent data (for example, it should be able to retrieve the "current" President of the USA and also previous presidents if asked). I'm thinking this Knowledge Graph could be used for Retrieval Augmented Generation (RAG) to help with business goals or maybe used with more clever User Interfaces (UIs). I'm not sure how to build or populate this KG and also have a rough idea of how to use it. Can you help me with suggesting particular paths for building and populating this Knowledge Graph?

Knowledge Graphs in Biology

In this clip

From this podcast

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Machine Learning at GSK with Kim Branson - #536

Related Questions