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Paper Details

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.
Brief Bioinform
0
2023
-, AD, Alzheimer's disease, associated genes, cognitive impairment, dementia, neurodegenerative diseases, patient
Alzheimer Disease, Cognitive Dysfunction, Deep Learning, Humans, Magnetic Resonance Imaging, Mutation
Author NameAffiliation
Xingxin PanLivestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin
Zeynep Coban AkdemirSchool of Public Health, The University of Texas Health Science Center at Houston
Ruixuan GaoUniversity of Illinois Chicago
Xiaoqian JiangUniversity of Texas Health Science Center
Gloria M Sheynkman (CM4AI)University of Virginia
Gloria M Sheynkman (CM4AI)University of Virginia
Gloria M Sheynkman (CM4AI)Center for Public Health Genomics, and UVA Comprehensive Cancer Center, University of Virginia
Erxi WuLivestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin
Erxi WuNeuroscience Institute and Department of Neurosurgery
Erxi WuTexas A & M University Health Science Center, College of Medicine
Erxi WuDepartment of Pharmaceutical Sciences, Texas A & M University Health Science Center, College Station
Jason H HuangNeuroscience Institute and Department of Neurosurgery
Jason H HuangTexas A & M University Health Science Center, College of Medicine
Nidhi SahniThe University of Texas MD Anderson Cancer Center
Nidhi SahniThe University of Texas MD Anderson Cancer Center
Nidhi SahniBaylor College of Medicine
S Stephen YiLivestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin
S Stephen YiOden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin
S Stephen YiCollege of Natural Sciences, The University of Texas at Austin
S Stephen YiThe University of Texas at Austin
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