Partanen JJ, Häppölä P, Zhou W, et al. Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics. Cell genomics. 2022;2(10):100181. doi:10.1016/j.xgen.2022.100181
Publications
Brumpton BM, Graham S, Surakka I, et al. The HUNT study: A population-based cohort for genetic research. Cell genomics. 2022;2(10):100193. doi:10.1016/j.xgen.2022.100193
Namba S, Konuma T, Wu KH, Zhou W, Initiative GBM analysis, Okada Y. A practical guideline of genomics-driven drug discovery in the era of global biobank meta-analysis. Cell genomics. 2022;2(10):100190. doi:10.1016/j.xgen.2022.100190
Tsuo K, Zhou W, Wang Y, et al. Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity. Cell genomics. 2022;2(12):100212. doi:10.1016/j.xgen.2022.100212
Florez JC. Genomic discoveries unveil mechanistic insights in diabetes. Cell genomics. 2022;2(12):100230. doi:10.1016/j.xgen.2022.100230
Wigdor EM, Weiner DJ, Grove J, et al. The female protective effect against autism spectrum disorder. Cell genomics. 2022;2(6):100134. doi:10.1016/j.xgen.2022.100134
Collins R, Balaconis MK, Brunak S, et al. Global priorities for large-scale biomarker-based prospective cohorts. Cell genomics. 2022;2(6):100141. doi:10.1016/j.xgen.2022.100141
Karczewski KJ, Solomonson M, Chao KR, et al. Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841Â UK Biobank exomes. Cell genomics. 2022;2(9):100168. doi:10.1016/j.xgen.2022.100168
Orsi D, Pook E, Bräuer N, et al. Discovery and Structure-Based Design of Potent Covalent PPARγ Inverse-Agonists and . Journal of medicinal chemistry. 2022;65(21):14843-14863. doi:10.1021/acs.jmedchem.2c01379
Way G, Natoli T, Adeboye A, et al. Morphology and gene expression profiling provide complementary information for mapping cell state. Cell systems. 2022;13(11):911-923.e9. doi:10.1016/j.cels.2022.10.001