A5022408570- Radiomics and Machine Learning in Medical Imaging
- Cancer Research and Treatments
- Cancer, Hypoxia, and Metabolism
- Single-cell and spatial transcriptomics
- Genomics and Phylogenetic Studies
- Cancer Immunotherapy and Biomarkers
- Gene expression and cancer classification
- RNA and protein synthesis mechanisms
- Bioinformatics and Genomic Networks
- Machine Learning in Bioinformatics
- RNA modifications and cancer
- Colorectal Cancer Treatments and Studies
- MicroRNA in disease regulation
- Synthesis and bioactivity of alkaloids
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
- Circular RNAs in diseases
- Advanced X-ray and CT Imaging
- Genomics and Chromatin Dynamics
- Gene Regulatory Network Analysis
- Alzheimer's disease research and treatments
- Melanoma and MAPK Pathways
- Neuroinflammation and Neurodegeneration Mechanisms
- Bacterial Genetics and Biotechnology
- Cancer therapeutics and mechanisms
The Ohio State University
2018-2025
The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute
2022-2025
Sichuan University
2022-2025
West China Hospital of Sichuan University
2022-2025
Guiyang Medical University
2022-2025
Air Force Medical University
2025
Chinese Academy of Sciences
2001-2024
Walla Walla University
2015-2024
University of Chinese Academy of Sciences
2017-2024
Guangdong Academy of Agricultural Sciences
2022-2024
Abstract Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, complex diseases, but its analyses still suffer from multiple grand challenges, including sequencing sparsity differential patterns in gene expression. We introduce scGNN (single-cell graph neural network) provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This formulates aggregates cell–cell relationships with networks models heterogeneous...
Biclustering extends the traditional clustering techniques by attempting to find (all) subgroups of genes with similar expression patterns under to-be-identified subsets experimental conditions when applied gene data. Still real power this strategy is yet be fully realized due lack effective and efficient algorithms for reliably solving general biclustering problem. We report a QUalitative BIClustering algorithm (QUBIC) that can solve problem in more form, compared existing algorithms,...
Abstract Motivation Mitochondria are an essential organelle in most eukaryotes. They not only play important role energy metabolism but also take part many critical cytopathological processes. Abnormal mitochondria can trigger a series of human diseases, such as Parkinson's disease, multifactor disorder and Type-II diabetes. Protein submitochondrial localization enables the understanding protein function studying disease pathogenesis drug design. Results We proposed new method,...
Traumatic spinal cord injury (SCI) triggers a neuro-inflammatory response dominated by tissue-resident microglia and monocyte derived macrophages (MDMs). Since activated MDMs are morphologically identical express similar phenotypic markers in vivo, identifying responses specifically coordinated has historically been challenging. Here, we pharmacologically depleted use anatomical, histopathological, tract tracing, bulk single cell RNA sequencing to reveal the cellular molecular SCI controlled...
Sex bias exists in the development and progression of nonreproductive organ cancers, but underlying mechanisms are enigmatic. Studies so far have focused largely on sexual dimorphisms cancer biology socioeconomic factors. Here, we establish a role for CD8+ T cell-dependent antitumor immunity mediating sex differences tumor aggressiveness, which is driven by gonadal androgen not chromosomes. A male frequency intratumoral antigen-experienced Tcf7/TCF1+ progenitor exhausted cells that devoid...
The metabolic heterogeneity and interplay between cells are known as significant contributors to disease treatment resistance. However, with the lack of a mature high-throughput single-cell metabolomics technology, we yet establish systematic understanding intra-tissue cooperative mechanisms. To mitigate this knowledge gap, developed novel computational method, namely, flux estimation analysis (scFEA), infer cell-wise fluxome from RNA-sequencing (scRNA-seq) data. scFEA is empowered by...
Abstract Drug screening data from massive bulk gene expression databases can be analyzed to determine the optimal clinical application of cancer drugs. The growing amount single-cell RNA sequencing (scRNA-seq) also provides insights into improving therapeutic effectiveness by helping study heterogeneity drug responses for cell subpopulations. Developing computational approaches predict and interpret response in collected samples very useful. We propose scDEAL, a deep transfer learning...
Abstract Single-cell multi-omics (scMulti-omics) allows the quantification of multiple modalities simultaneously to capture intricacy complex molecular mechanisms and cellular heterogeneity. Existing tools cannot effectively infer active biological networks in diverse cell types response these external stimuli. Here we present DeepMAPS for network inference from scMulti-omics. It models scMulti-omics a heterogeneous graph learns relations among cells genes within both local global contexts...
Abstract Accurately predicting peptide secondary structures remains a challenging task due to the lack of discriminative information in short peptides. In this study, PHAT is proposed, deep hypergraph learning framework for prediction and exploration downstream tasks. The includes novel interpretable multi‐head attention network that uses residue‐based reasoning structure prediction. algorithm can incorporate sequential semantic from large‐scale biological corpus structural multi‐scale...
Abstract Increasing drought frequency and severity in a warming climate threaten forest ecosystems with widespread tree deaths. Canopy structure is important regulating mortality during drought, but how it functions remains controversial. Here, we show that the interplay between size explains drought-induced 2012-2016 California drought. Through an analysis of over one million trees, find rate follows “negative-positive-negative” piecewise relationship height, maintains consistent negative...
Abstract Alzheimer’s Disease (AD) pathology has been increasingly explored through single-cell and single-nucleus RNA-sequencing (scRNA-seq & snRNA-seq) spatial transcriptomics (ST). However, the surge in data demands a comprehensive, user-friendly repository. Addressing this, we introduce RNA-seq database for disease (ssREAD). It offers broader spectrum of AD-related datasets, an optimized analytical pipeline, improved usability. The encompasses 1,053 samples (277 integrated datasets)...
Abstract Rare cell populations are key in neoplastic progression and therapeutic response, offering potential intervention targets. However, their computational identification analysis often lag behind major types. To fill this gap, we introduce MarsGT: Multi-omics Analysis for population inference using a Single-cell Graph Transformer. It identifies rare probability-based heterogeneous graph transformer on single-cell multi-omics data. MarsGT outperforms existing tools identifying cells...