A5032177649- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Single-cell and spatial transcriptomics
- Functional Brain Connectivity Studies
- Microbial Metabolic Engineering and Bioproduction
- Dementia and Cognitive Impairment Research
- Genetics, Bioinformatics, and Biomedical Research
- Genetic Associations and Epidemiology
- RNA Research and Splicing
- Cancer-related molecular mechanisms research
Shandong University
2024
Qufu Normal University
2022-2023
In this study, we proposed a novel method called the graph capsule convolutional network (GCCN) to predict progression from mild cognitive impairment dementia and identify its pathogenesis. First, risk gene discovery component indirectly target genes with higher interactions others. These brain regions were collected as nodes construct heterogeneous pathogenic information association graphs. Second, capsules established by projecting into set of disentangled latent components. The...
Alzheimer's disease (AD) is a highly inheritable neurological disorder, and brain imaging genetics (BIG) has become rapidly advancing field for comprehensive understanding its pathogenesis. However, most of the existing approaches underestimate complexity interactions among factors that cause AD. To take full appreciate these interactions, we propose BIGFormer, graph Transformer with local structural awareness, AD diagnosis identification pathogenic mechanisms. Specifically, interaction...
Abstract Background Deciphering spatial domains using spatially resolved transcriptomics (SRT) is of great value for characterizing and understanding tissue architecture. However, the inherent heterogeneity varying resolutions present challenges in joint analysis multimodal SRT data. Results We introduce a geometric deep learning method, named stMMR, to effectively integrate gene expression, location, histological information accurate identifying from stMMR uses graph convolutional networks...
ABSTRACT Spatial omics technologies have revolutionized our studies on tissue architecture and cellular interactions at single-cell resolution. While spatial multi-omics approaches offer unprecedented insights into complex biological systems, their widespread adoption is hindered by technical challenges, specialized requirements, limited accessibility. To address these limitations, we present NicheTrans, the first spatially-aware cross-omics translation method a flexible Transformer-based...