My research examines how human genetic variation is related to the prevalence of complex traits and diseases, with a particular focus on cardiovascular diseases. 

I am especially interested in how multi-omic data from different tissue sources can be modelled as molecular networks. This approach aims to address the mechanistic deficit connecting genotype to phenotype, which is often present in studies based on observational data. I am also interested in how different causal inference methods can be applied in such contexts, and their potential impact on translational research. 

Academic article

• Mocci, Giuseppe; Sukhavasi, Katyayani; Örd, Tiit et al. (2024). Single-Cell Gene-Regulatory Networks of Advanced Symptomatic Atherosclerosis. (external link)
• Bankier, Sean Alexander; Wang, Lingfei; Crawford, Andrew et al. (2023). Plasma cortisol-linked gene networks in hepatic and adipose tissues implicate corticosteroid-binding globulin in modulating tissue glucocorticoid action and cardiovascular risk. (external link)
• Bankier, Sean Alexander; Michoel, Tom (2022). eQTLs as causal instruments for the reconstruction of hormone linked gene networks. (external link)

See a complete overview of publications in Cristin.

Avaliable at: https://scholar.google.com/citations?user=tsa5dR8AAAAJ&hl=en