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Machine learning prediction and tau-based screening identifies potential Alzheimer’s disease genes relevant to immunity

Authors :
Jessica Binder
Oleg Ursu
Cristian Bologa
Shanya Jiang
Nicole Maphis
Somayeh Dadras
Devon Chisholm
Jason Weick
Orrin Myers
Praveen Kumar
Jeremy J. Yang
Kiran Bhaskar
Tudor I. Oprea
Source :
Communications Biology, Vol 5, Iss 1, Pp 1-15 (2022)
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Jessica Binder et al. developed a machine learning model to discover potential drug targets for Alzheimer’s disease. They validated their 20 top candidates in several in vitro models, and highlight FRRS1, CTRAM, SCGB3A1, FAM92B/CIBAR2, and TMEFF2 as potential AD risk genes.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
23993642
Volume :
5
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Communications Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.fe528a0fb444148715ee8fe57ec23e
Document Type :
article
Full Text :
https://doi.org/10.1038/s42003-022-03068-7