Dr. Leslie Myint

Project Title: 
Causal Discovery From Text Data

Science moves fast, and it can be difficult to keep pace. Reading, understanding, and being able to quickly draw on scientific advances in one's own work is a crucial, but extraordinarily time-intensive, part of scholarly work. 

The main goal of this project is to reconstruct causal models from text (e.g., scholarly papers) within the biological sciences. The researchers leverage a database called Semantic Medline that contains millions of "predications" (essentially correlative links between ideas) from abstracts of biomedical literature available on PubMed.

The specific goals of this research are:

  • To construct graphical causal models from this text data in specific biology focus areas (e.g., specific human diseases)
  • To validate these models using high-throughput measurements (e.g., genomics, transcriptomics, metabolomics, proteomics)
  • To facilitate the proposal of key experiments that would most substantially reduce the uncertainty in learned models

Project Investigators

Dr. Leslie Myint
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