アルツハイマー病におけるTRIM11アップレギュレーターの治療標的としての特定：ベイジアンネットワークアプローチ

A recent study shows that TRIM11 is downregulated in Alzheimer's Disease (AD) but has been demonstrated to improve cognitive function when overexpressed in mouse AD models. Based on this discovery, our study aims to identify potential genetic regulators of TRIM11 using single-cell and single-nucleus RNA sequencing, and graph learning methods. In this study we explore two publicly available datasets: GSE173731 and GSE227222. To identify the potential regulators of TRIM11, we use a probabilistic approach and Bayesian networks. Our approach identified a set of candidate genes in both datasets that may exert regulatory influence on TRIM11, offering potential targets for further research in future therapeutic strategies in AD.