Regret Detection on Social Media using BERT-BiLSTM Model DOI
Renuka Sharma,

Sushama Nagpal,

Sangeeta Sabharwal

et al.

Published: Aug. 23, 2024

Language: Английский

From genes to drugs: targeting Alzheimer’s with circadian insights DOI Creative Commons
Zekun Li, Xiaohan Li, Lei Su

et al.

Frontiers in Aging Neuroscience, Journal Year: 2025, Volume and Issue: 17

Published: March 26, 2025

Background Alzheimer’s disease (AD) is a typical neurodegenerative that presents challenges due to the lack of biomarkers identify AD. A growing body evidence highlights critical role circadian rhythms in Methods The differentially expressed clock genes (DECGs) were identified between AD and ND groups (non-demented controls). Functional enrichment analysis was executed on DECGs. Candidate diagnostic for screened by machine learning. ROC nomograms constructed evaluate candidate biomarkers. In addition, therapeutics targeting predictive through DGIdb website. Finally, mRNA–miRNA network constructed. Results Nine DECG groups. Enrichment nine indicated pathways enriched long-term potentiation entrainment. Four (GSTM3, ERC2, PRKCG, HLA-DMA) using Lasso regression, random forest, SVM, GMM. performance four evaluated curve. Furthermore, nomogram HLA-DMA are good diagnosing Single-gene GSEA main oxidative phosphorylation, neurodegeneration-multiple diseases, etc. results immune cell infiltration there significant differences 15 subsets Moreover, 23 drugs 8 PRKCG Conclusion We three associated with genes, thus providing promising therapeutic targets

Language: Английский

Citations

0

Regret Detection on Social Media using BERT-BiLSTM Model DOI
Renuka Sharma,

Sushama Nagpal,

Sangeeta Sabharwal

et al.

Published: Aug. 23, 2024

Language: Английский

Citations

0