A5100704670- Advanced biosensing and bioanalysis techniques
- RNA and protein synthesis mechanisms
- RNA Interference and Gene Delivery
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Applications
- Advanced Image and Video Retrieval Techniques
- Single-cell and spatial transcriptomics
- Pharmacological Effects of Natural Compounds
- Advanced Biosensing Techniques and Applications
- Biosensors and Analytical Detection
- DNA and Nucleic Acid Chemistry
- Advanced Vision and Imaging
- Radiomics and Machine Learning in Medical Imaging
- Lung Cancer Diagnosis and Treatment
- Monoclonal and Polyclonal Antibodies Research
- Natural product bioactivities and synthesis
- Lung Cancer Treatments and Mutations
- Bioinformatics and Genomic Networks
- MicroRNA in disease regulation
- RNA Research and Splicing
- Medicinal Plants and Bioactive Compounds
- Reinforcement Learning in Robotics
- Ginseng Biological Effects and Applications
- Computational Drug Discovery Methods
- Molecular Biology Techniques and Applications
Shanghai Maritime University
2025
Shandong University
2024
Sun Yat-sen University
2023-2024
Hong Kong Baptist University
2016-2023
Shenzhen Institute for Drug Control
2016-2017
University of Macau
2013
Several virtual screening models are proposed to screen small molecules only targeting primary miRNAs without selectivity. Few attempts have been made develop strategies for discovering mature miRNAs. Mature and their specific target mRNA can form unique functional loops during argonaute (AGO)-mediated miRNA-mRNA interactions, which may serve as potential targets small-molecule drug discovery. Thus, a loop-based AGO-incorporated model is constructed the loops. The previously published...
Abstract Spatial transcriptomics (ST) has emerged as a transformative approach for comprehending tissue architecture with molecular profiles. However, amalgamating discrete two-dimensional (2D) ST snapshots into unified 3D atlas remains an outstanding challenge. To this end, we introduce STAIR, end-to-end solution alignment, integration, and de novo reconstruction. STAIR uses heterogeneous graph attention network spot-level slice-level mechanisms to obtain embedding space guide...
Abstract Motivation Accurate identification of spatial domains is essential for analyzing transcriptomics data to elucidate tissue microenvironments and biological functions. Existing methods utilize either local or global relationships between spots aid domain segmentation. A method that can concurrently capture both information may improve domains. Results In this article, we propose SECE, a deep learning-based captures among aggregates their using expression similarity similarity. We...
We developed an interpretable model, BOUND (Bayesian netwOrk for large-scale lUng caNcer Digital prescreening), using a comprehensive EHR dataset from the China to improve lung cancer detection rates. employs Bayesian network uncertainty inference, allowing it predict risk even with missing data and identify high-risk factors. Developed 905,194 individuals, achieved AUC of 0.866 in internal validation, time- geography-based external validations yielding AUCs 0.848 0.841, respectively. In...
Nowadays, with the development of nature drug, herbal medicine is gaining more attention from scientists in various countries. In China, ancient ethnomedicine based on natural medicinal plants faces new opportunities and challenges. This paper examines Li ethnomedicine, which has not attracted much among researchers yet. Four special species, had important significance for modern research were very helpful treating diseases, such as cancer, cardiovascular, cerebrovascular disease, selected a...