Computational biology and big data analytics

Renato Polimanti's primary research interest is to apply big data analytics to molecular, clinical, and imaging data to understand the biology and epidemiology of neuropsychiatric disorders, behavioral traits, and other complex phenotypes, and to develop tools to improve healthcare for diverse population groups.

Methods

computational modeling ;  epidemiology ;  epigenetics ;  genomics ;  meta analysis ;  statistical methods  

Topics

aging ;  cognition ;  genetics ;  mental health ;  predictive modeling ;  stress  

Biography

Polimanti is an Associate Professor at Yale University School of Medicine. He received his PhD in evolutionary biology from the University of Rome "Tor Vergata" in October 2013. Subsequently, he completed his postdoctoral training in biological psychiatry at Yale. In July 2017, Polimanti began his independent career in the Division of Human Genetics of the Yale Department of Psychiatry.

Research Contributions

Genetically regulated multi-omics study for symptom clusters of posttraumatic stress disorder highlights pleiotropy with hematologic and cardio-metabolic traits

Mol Psychiatry (2022)

The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

International Journal of Epidemiology (2022)

An Atlas of Genetic Correlations and Genetically Informed Associations Linking Psychiatric and Immune-Related Phenotypes

JAMA Psychiatry (2022)

Multivariate genome-wide analysis of education, socioeconomic status and brain phenome

Nature Human Behaviour (2021)

Association of Economic Status and Educational Attainment With Posttraumatic Stress Disorder: A Mendelian Randomization Study

JAMA Network Open (2019)