دورية أكاديمية

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.

التفاصيل البيبلوغرافية
العنوان: AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.
المؤلفون: Pan, Xingxin, Akdemir, Zeynep H Coban, Gao, Ruixuan, Jiang, Xiaoqian, Sheynkman, Gloria M, Wu, Erxi, Huang, Jason H, Sahni, Nidhi, Yi, S Stephen
المصدر: Briefings in Bioinformatics; Mar2023, Vol. 24 Issue 2, p1-12, 12p
مصطلحات موضوعية: DEEP learning, ALZHEIMER'S disease, GENETIC mutation, NEURODEGENERATION, INDIVIDUALIZED medicine
مستخلص: Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient sample size and selection bias. There is a lack of comprehensive research aimed to identify AD-associated risk mutations systematically. To address this challenge, we hereby construct a large-scale AD mutation and co-mutation framework ('AD-Syn-Net'), and propose deep learning models named Deep-SMCI and Deep-CMCI configured with fully connected layers that are capable of predicting cognitive impairment of subjects effectively based on genetic mutation and co-mutation profiles. Next, we apply the customized frameworks to data sets to evaluate the importance scores of the mutations and identified mutation effectors and co-mutation combination vulnerabilities contributing to cognitive impairment. Furthermore, we evaluate the influence of mutation pairs on the network architecture to dissect the genetic organization of AD and identify novel co-mutations that could be responsible for dementia, laying a solid foundation for proposing future targeted therapy for AD precision medicine. Our deep learning model codes are available open access here: https://github.com/Pan-Bio/AD-mutation-effectorsTest. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Complementary Index
الوصف
تدمد:14675463
DOI:10.1093/bib/bbad030