1. Westerman, Kenneth E, Pham, Duy T, Hong, Liang, Chen, Han, Manning, Alisa K. . GEM: scalable and flexible gene-environment interaction analysis in millions of samples. In Bioinformatics (Oxford, England), 37, 3514-3520. doi:10.1093/bioinformatics/btab223. https://pubmed.ncbi.nlm.nih.gov/34695175/
2. Mishra, Mrinal, Nahlawi, Layan, Zhong, Yizhen, Alarcon, Cristina, Perera, Minoli A. . LA-GEM: imputation of gene expression with incorporation of Local Ancestry. In Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 29, 341-358. doi:. https://pubmed.ncbi.nlm.nih.gov/38160291/
3. Zhang, Ting-He, Hasib, Md Musaddaqul, Chiu, Yu-Chiao, Chen, Yidong, Huang, Yufei. 2022. Transformer for Gene Expression Modeling (T-GEM): An Interpretable Deep Learning Model for Gene Expression-Based Phenotype Predictions. In Cancers, 14, . doi:10.3390/cancers14194763. https://pubmed.ncbi.nlm.nih.gov/36230685/
4. . . CAG Repeat Not Polyglutamine Length Determines Timing of Huntington's Disease Onset. In Cell, 178, 887-900.e14. doi:10.1016/j.cell.2019.06.036. https://pubmed.ncbi.nlm.nih.gov/31398342/
5. Xi, Yun, Chen, Hong, Xi, Yue, Zhang, Min, Li, Biao. 2023. Visualization research on ENT1/NIS dual-function gene therapy to reverse drug resistance mediated by MUC1 in GEM-resistant pancreatic cancer. In Nuclear medicine and biology, 120-121, 108350. doi:10.1016/j.nucmedbio.2023.108350. https://pubmed.ncbi.nlm.nih.gov/37229950/
6. Thanamit, Kulwadee, Hoerhold, Franziska, Oswald, Marcus, Koenig, Rainer. 2022. Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis. In BMC bioinformatics, 23, 226. doi:10.1186/s12859-022-04742-7. https://pubmed.ncbi.nlm.nih.gov/35689204/
7. De La Vega, Francisco M, Chowdhury, Shimul, Moore, Barry, Yandell, Mark, Kingsmore, Stephen F. 2021. Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases. In Genome medicine, 13, 153. doi:10.1186/s13073-021-00965-0. https://pubmed.ncbi.nlm.nih.gov/34645491/
8. . . Identification of Genetic Factors that Modify Clinical Onset of Huntington's Disease. In Cell, 162, 516-26. doi:10.1016/j.cell.2015.07.003. https://pubmed.ncbi.nlm.nih.gov/26232222/