1. Mullin, Benjamin H, Zhu, Kun, Brown, Suzanne J, Xu, Jiake, Wilson, Scott G. . Leveraging osteoclast genetic regulatory data to identify genes with a role in osteoarthritis. In Genetics, 225, . doi:10.1093/genetics/iyad150. https://pubmed.ncbi.nlm.nih.gov/37579195/
2. Palumbo, Orazio, Palumbo, Pietro, Ferri, Emanuela, Carella, Massimo, Di Giacomo, Marilena Carmela. 2015. Report of a patient and further clinical and molecular characterization of interstitial 4p16.3 microduplication. In Molecular cytogenetics, 8, 15. doi:10.1186/s13039-015-0119-6. https://pubmed.ncbi.nlm.nih.gov/25774220/
3. Wu, I-Wen, Tsai, Tsung-Hsien, Lo, Chi-Jen, Sytwu, Huey-Kang, Tsai, Ting-Fen. 2022. Discovering a trans-omics biomarker signature that predisposes high risk diabetic patients to diabetic kidney disease. In NPJ digital medicine, 5, 166. doi:10.1038/s41746-022-00713-7. https://pubmed.ncbi.nlm.nih.gov/36323795/
4. Fagerholm, Rainer, Khan, Sofia, Schmidt, Marjanka K, Blomqvist, Carl, Nevanlinna, Heli. . TP53-based interaction analysis identifies cis-eQTL variants for TP53BP2, FBXO28, and FAM53A that associate with survival and treatment outcome in breast cancer. In Oncotarget, 8, 18381-18398. doi:10.18632/oncotarget.15110. https://pubmed.ncbi.nlm.nih.gov/28179588/
5. Li, Siting, Gui, Jiang, Karagas, Margaret R, Passarelli, Michael N. 2025. Transcriptome-wide association study identifies genes associated with bladder cancer risk. In Scientific reports, 15, 1390. doi:10.1038/s41598-025-85565-3. https://pubmed.ncbi.nlm.nih.gov/39789109/