"Linkage Disequilibrium-Informed Deep Learning Framework for Alzheimer's Disease" This study introduces Deep-Block, a novel multi-stage deep learning framework that incorporates biological knowledge for analyzing large-scale genomic data in Alzheimer's disease. Applied to the Alzheimer's Disease Sequencing Project (ADSP) dataset of 7,416 participants, the framework successfully identif...
Dr. Jo and colleagues published a research paper titled "Circular-SWAT for Deep Learning Based Diagnostic Classification of Alzheimer's Disease: Application to Metabolome Data" in eBioMedicine (doi: 10.1016/j.ebiom.2023.104820) in October 2023. The study introduced a novel Circular-Sliding Window Association Test (c-SWAT) methodology to improve classification accuracy in predicting Alzheimer&#...
Dr. Jo and colleagues published a research paper titled "Deep Learning-based Identification of Genetic Variants: Application to Alzheimer's Disease Classification" in Briefings in Bioinformatics in 2022 (doi: 10.1093/bib/bbac022). The study introduced a novel deep learning-based approach to identify genetic variants associated with Alzheimer's disease, demonstrating effective classificatio...
[2021/04/05] Research Publication: Advances and Challenges in AlphaFold2
Dr. Jo published a comprehensive review article titled "Advances and Challenges in AlphaFold2" in Physics and High Technology in 2021. The article provided an in-depth analysis of the developments and current limitations in AlphaFold2's protein structure prediction capabilities.
Dr. Jo, along with colleagues, published a research paper titled "Deep Learning Detection of Informative Features in tau PET for Alzheimer's Disease Classification" in BMC Bioinformatics (doi: 10.1186/s12859-020-03848-0) in 2020. The study developed a deep learning-based framework combining 3D CNN and LRP algorithms to identify informative features in tau PET images for Alzheimer's disease...
Dr. Jo, along with colleagues, published a systematic review paper titled "Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data" in Frontiers in Aging Neuroscience (doi: 10.3389/fnagi.2019.00220) on August 20, 2019. This comprehensive review examined the application of deep learning approaches in neuroimaging data for improving Alzhe...
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