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

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.

Bibliographic Details
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
Format: Article
Language:English
Published: Nature Portfolio 2022-02-01
Series:Communications Biology
Online Access:https://doi.org/10.1038/s42003-022-03068-7

Internet

https://doi.org/10.1038/s42003-022-03068-7

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