Probabilistic computational causal discovery for systems biology

​Discovering the causal mechanisms of biological systems is necessary to design new drugs and therapies. Computational Causal Discovery (CD) is a field that offers the potential to discover causal relations and causal models under certain conditions with a limited set of interventions/manipulations. This chapter reviews the basic concepts and principles of CD, the nature of the assumptions to enable it, potential pitfalls in its application, and recent advances and directions. Importantly, several success stories in molecular and systems biology are discussed in detail.

DOI: 10.1007/978-3-319-21296-8_3

Probabilistic computational causal discovery for systems biology .pdf