1. Kumpula, Timo A, Vorimo, Sandra, Mattila, Taneli T, Mantere, Tuomo, Pylkäs, Katri. 2023. Exome sequencing identified rare recurrent copy number variants and hereditary breast cancer susceptibility. In PLoS genetics, 19, e1010889. doi:10.1371/journal.pgen.1010889. https://pubmed.ncbi.nlm.nih.gov/37578974/
2. Gao, Siyuan, Zhao, Jing, Xu, Qinglei, Schinckel, Allan P, Zhou, Bo. 2021. MiR-31 targets HSD17B14 and FSHR, and miR-20b targets HSD17B14 to affect apoptosis and steroid hormone metabolism of porcine ovarian granulosa cells. In Theriogenology, 180, 94-102. doi:10.1016/j.theriogenology.2021.12.014. https://pubmed.ncbi.nlm.nih.gov/34959084/
3. Mychaleckyj, Josyf C, Valo, Erkka, Ichimura, Takaharu, Warram, James H, Krolewski, Andrzej S. 2021. Association of Coding Variants in Hydroxysteroid 17-beta Dehydrogenase 14 (HSD17B14) with Reduced Progression to End Stage Kidney Disease in Type 1 Diabetes. In Journal of the American Society of Nephrology : JASN, 32, 2634-2651. doi:10.1681/ASN.2020101457. https://pubmed.ncbi.nlm.nih.gov/34261756/
4. Qureshi, Rehana, Picon-Ruiz, Manuel, Sho, Maiko, Ince, Tan A, Slingerland, Joyce. . Estrone, the major postmenopausal estrogen, binds ERa to induce SNAI2, epithelial-to-mesenchymal transition, and ER+ breast cancer metastasis. In Cell reports, 41, 111672. doi:10.1016/j.celrep.2022.111672. https://pubmed.ncbi.nlm.nih.gov/36384125/
5. Zhou, Julie Xia, Li, Linda Xiaoyan, Zhang, Hongbing, Calvet, James P, Li, Xiaogang. 2024. DNA methyltransferase 1 (DNMT1) promotes cyst growth and epigenetic age acceleration in autosomal dominant polycystic kidney disease. In Kidney international, 106, 258-272. doi:10.1016/j.kint.2024.04.017. https://pubmed.ncbi.nlm.nih.gov/38782200/
6. Kordshouli, Shirin Omidvar, Tahmasebi, Ahmad, Moghadam, Ali, Ramezani, Amin, Niazi, Ali. 2024. A comprehensive meta-analysis of transcriptome data to identify signature genes associated with pancreatic ductal adenocarcinoma. In PloS one, 19, e0289561. doi:10.1371/journal.pone.0289561. https://pubmed.ncbi.nlm.nih.gov/38324544/
7. Bi, Z, Wang, L-J, Lin, Y-X, Wang, S-H, Fang, Z-H. . Development of a clinical prediction model for diabetic kidney disease with glucose and lipid metabolism disorders based on machine learning and bioinformatics technology. In European review for medical and pharmacological sciences, 28, 863-878. doi:10.26355/eurrev_202402_35324. https://pubmed.ncbi.nlm.nih.gov/38375694/