Sean Hackett

I am interested in using high-dimensional data to construct causal networks of interconnected molecular and phenotypic features and understanding how perturbations propagate across these networks causing diseases and aging. I also help to develop Calico’s capabilities for computational mass spectrometry, both to cast a wide net in search of biomarkers, but also so we can build principled integrative-omic models.

I spent my PhD developing methods for understanding metabolism at the interface of fluxes, metabolites and enzymes using high-dimensional data. I devoted my PostDoc to developing techniques for extracting additional information from such data modalities.

Publications

Time-resolved genome-scale profiling reveals a causal expression network

Systems-level analysis of mechanisms regulating yeast metabolic flux

Genetic basis of metabolome variation in yeast

Education

Princeton University, Ph.D. in Quantitative and Computational Biology

Cornell University, B.S. in Biological Sciences (Genetics & Development)

Honors and Awards

MIT Sloan Sports Analytics Conference Research Paper Finalist - 2017

Department of Energy Office of Science Graduate Fellow - 2012