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.

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Detaylı Bibliyografya
Asıl Yazarlar:	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
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Nature Portfolio 2022-02-01
Seri Bilgileri:	Communications Biology
Online Erişim:	https://doi.org/10.1038/s42003-022-03068-7
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

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

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