[HTML][HTML] Artificial intelligence in COVID-19 drug repurposing

Y Zhou, F Wang, J Tang, R Nussinov… - The Lancet Digital …, 2020 - thelancet.com
Drug repurposing or repositioning is a technique whereby existing drugs are used to treat
emerging and challenging diseases, including COVID-19. Drug repurposing has become a …

AlphaFold, artificial intelligence (AI), and allostery

R Nussinov, M Zhang, Y Liu, H Jang - The Journal of Physical …, 2022 - ACS Publications
AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of
biological sequence data and artificial intelligence (AI). AlphaFold has appended projects …

Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer's …

J Fang, P Zhang, Y Zhou, CW Chiang, J Tan, Y Hou… - Nature Aging, 2021 - nature.com
We developed an endophenotype disease module-based methodology for Alzheimer's
disease (AD) drug repurposing and identified sildenafil as a potential disease risk modifier …

[HTML][HTML] Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment

Y Zhou, J Xu, Y Hou, JB Leverenz, A Kallianpur… - Alzheimer's research & …, 2021 - Springer
Background Dementia-like cognitive impairment is an increasingly reported complication of
SARS-CoV-2 infection. However, the underlying mechanisms responsible for this …

[HTML][HTML] Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease

J Xu, C Mao, Y Hou, Y Luo, JL Binder, Y Zhou… - Cell reports, 2022 - cell.com
Translating human genetic findings (genome-wide association studies [GWAS]) to
pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease …

[HTML][HTML] The promise of microRNA-based therapies in Alzheimer's disease: challenges and perspectives

H Walgrave, L Zhou, B De Strooper, E Salta - Molecular …, 2021 - Springer
Multi-pathway approaches for the treatment of complex polygenic disorders are emerging as
alternatives to classical monotarget therapies and microRNAs are of particular interest in …

Association predictions of genomics, proteinomics, transcriptomics, microbiome, metabolomics, pathomics, radiomics, drug, symptoms, environment factor, and …

Y Pan, X Lei, Y Zhang - Medicinal research reviews, 2022 - Wiley Online Library
Currently, the research of multi‐omics, such as genomics, proteinomics, transcriptomics,
microbiome, metabolomics, pathomics, and radiomics, are hot spots. The relationship …

Applied machine learning in Alzheimer's disease research: omics, imaging, and clinical data

Z Li, X Jiang, Y Wang, Y Kim - Emerging topics in life sciences, 2021 - portlandpress.com
Alzheimer's disease (AD) remains a devastating neurodegenerative disease with few
preventive or curative treatments available. Modern technology developments of high …

Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications …

J Xu, P Zhang, Y Huang, Y Zhou, Y Hou… - Genome …, 2021 - genome.cshlp.org
Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are
involved in the pathophysiology of Alzheimer's disease (AD), we systematically identified …

[HTML][HTML] Artificial intelligence for drug discovery and development in Alzheimer's disease

Y Qiu, F Cheng - Current Opinion in Structural Biology, 2024 - Elsevier
The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits
the development of effective therapeutics or prevention strategies. Artificial Intelligence (AI) …