School of Public Health


BioinformaticsBioinformatics involves the development and applications of computational tools and methods for understanding large and complex biological data.

Luningham JM, Chen J, Tang S, De Jager PL, Bennett DA, Buchman AS, Yang J. Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics. Am J Hum Genet. 2020 Oct 1;107(4):714-726. doi: 10.1016/j.ajhg.2020.08.022.

Luningham JM, McArtor DB, Hendriks AM, van Beijsterveldt CEM, Lichtenstein P, Lundström S, Larsson H, Bartels M, Boomsma DI, Lubke GH. Data Integration Methods for Phenotype Harmonization in Multi-Cohort Genome-Wide Association Studies with Behavioral Outcomes. Front Genet. 2019 Dec 10;10:1227. doi: 10.3389/fgene.2019.01227

Pathak, G. A., Silzer, T. K., Sun, J., Zhou, Z., Daniel, A. A., Johnson, L., … & Barber, R. C. (2019). Genome-wide methylation of mild cognitive impairment in mexican americans highlights genes involved in synaptic transport, alzheimer’s disease-precursor phenotypes, and metabolic morbidities. Journal of Alzheimer’s Disease, 72(3), 733-749.

Pathak, G. A., Zhou, Z., Silzer, T. K., Barber, R. C., Phillips, N. R., & Alzheimer’s Disease Neuroimaging Initiative, Breast and Prostate Cancer Cohort Consortium, and Alzheimer’s Disease Genetics Consortium. (2020). Two‐stage Bayesian GWAS of 9576 individuals identifies SNP regions that are targeted by miRNAs inversely expressed in Alzheimer’s and cancer. Alzheimer’s & Dementia, 16(1), 162-177.

Wu, G., Liu, L., Zhou, Z., Liu, J., Wang, B., Ruan, J., … & Wang, J. (2020). East Asian–Specific Common Variant in TNNI3 Predisposes to Hypertrophic Cardiomyopathy. Circulation, 142(21), 2086-2089.