1. Kriegova, Eva, Arakelyan, Arsen, Fillerova, Regina, du Bois, Roland M, Petrek, Martin. 2008. PSMB2 and RPL32 are suitable denominators to normalize gene expression profiles in bronchoalveolar cells. In BMC molecular biology, 9, 69. doi:10.1186/1471-2199-9-69. https://pubmed.ncbi.nlm.nih.gov/18671841/
2. He, Wei, Zhang, Zhe, Tan, ZiLong, Shen, XiaoLi, Zhu, XinGen. 2024. PSMB2 plays an oncogenic role in glioma and correlates to the immune microenvironment. In Scientific reports, 14, 5861. doi:10.1038/s41598-024-56493-5. https://pubmed.ncbi.nlm.nih.gov/38467767/
3. Liu, Zimeng, Yu, Changda, Chen, Zhibing, Ye, Lin, Li, Chen. 2022. PSMB2 knockdown suppressed proteasome activity and cell proliferation, promoted apoptosis, and blocked NRF1 activation in gastric cancer cells. In Cytotechnology, 74, 491-502. doi:10.1007/s10616-022-00538-y. https://pubmed.ncbi.nlm.nih.gov/36110152/
4. Krishnananthasivam, Shivankari, Jayathilaka, Nimanthi, Sathkumara, Harindra Darshana, Natesan, Mohan, De Silva, Aruna Dharshan. 2017. Host gene expression analysis in Sri Lankan melioidosis patients. In PLoS neglected tropical diseases, 11, e0005643. doi:10.1371/journal.pntd.0005643. https://pubmed.ncbi.nlm.nih.gov/28628607/
5. Tan, Sheng, Li, Hua, Zhang, Weijie, Sun, Jielin, Zhu, Tao. 2018. NUDT21 negatively regulates PSMB2 and CXXC5 by alternative polyadenylation and contributes to hepatocellular carcinoma suppression. In Oncogene, 37, 4887-4900. doi:10.1038/s41388-018-0280-6. https://pubmed.ncbi.nlm.nih.gov/29780166/
6. Taube, Magdalena, Andersson-Assarsson, Johanna C, Lindberg, Kristin, Eriksson, Jan W, Svensson, Per-Arne. 2015. Evaluation of reference genes for gene expression studies in human brown adipose tissue. In Adipocyte, 4, 280-5. doi:10.1080/21623945.2015.1039884. https://pubmed.ncbi.nlm.nih.gov/26451284/
7. Ghazaryan, Hovsep, Petrek, Martin, Boyajyan, Anna. 2014. Chronic schizophrenia is associated with over-expression of the interleukin-2 receptor gamma gene. In Psychiatry research, 217, 158-62. doi:10.1016/j.psychres.2014.03.020. https://pubmed.ncbi.nlm.nih.gov/24713359/
8. Li, Mingming, Wu, Lei. 2016. Functional analysis of keratinocyte and fibroblast gene expression in skin and keloid scar tissue based on deviation analysis of dynamic capabilities. In Experimental and therapeutic medicine, 12, 3633-3641. doi:10.3892/etm.2016.3817. https://pubmed.ncbi.nlm.nih.gov/28101157/
9. Zhou, Xi, Fan, Yu, Ye, Weiliang, Yang, Yuemei, Liu, Yong. 2020. Identification of the Novel Target Genes for Osteosarcoma Therapy Based on Comprehensive Bioinformatic Analysis. In DNA and cell biology, 39, 1172-1180. doi:10.1089/dna.2020.5377. https://pubmed.ncbi.nlm.nih.gov/32584170/
10. Chen, Q L, Qiao, F, Lu, W T, Shi, H L, Zhou, C X. . [Bioinformatics analysis of primary biliary cholangitis key genes and molecular mechanisms]. In Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology, 31, 1209-1216. doi:10.3760/cma.j.cn501113-20220315-00110. https://pubmed.ncbi.nlm.nih.gov/38238956/