Machine learning prediction and tau-based screening identifies potential Alzheimer’s disease genes relevant to immunity
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.
Main 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 |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-02-01
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Series: | Communications Biology |
Online Access: | https://doi.org/10.1038/s42003-022-03068-7 |
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