Optimal adjustment sets for causal query estimation in partially observed biomolecular networks.

Causal query estimation in biomolecular networks commonly selects a 'valid adjustment set', i.e. a subset of network variables that eliminates the bias of the estimator.

Do-calculus enables estimation of causal effects in partially observed biomolecular pathways.

Motivation: Estimating causal queries, such as changes in protein abundance in response to a perturbation, is a fundamental task in the analysis of biomolecular pathways. The estimation requires experimental measurements on the pathway components. However, in practice many pathway components are left unobserved (latent) because they are either unknown, or difficult to measure.