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Learning causal graphs under interventions and applications to single-cell biological data analysis
(Massachusetts Institute of Technology, 2021)
This thesis studies the problem of learning causal directed acyclic graphs (DAGs) in the setting where both observational and interventional data is available. This setting is common in biology, where gene regulatory ...
Using machine learning to increase the predictive value of humanized mouse models for the human immune response to YFV-17D
(Massachusetts Institute of Technology, 2021-06)
Despite their utility as models for human systems, intrinsic differences between mouse and human biology limit direct translation of findings. Immunocompromised mice have been engrafted with functional human immune system ...