Area of research
Molecular Biology · Computer Vision and Pattern Recognition
Research interest
Research focused on Disease and Graph, with related work in Identification (biology), Artificial intelligence, Interpretability. Notable publications include 'Balanced Contrastive Learning for Long-Tailed Visual Recognition', 'HyPyP: a Hyperscanning Python Pipeline for inter-brain connectivity analysis', and 'GANLDA: Graph attention network for lncRNA-disease associations prediction'.
The Large Language Models on Biomedical Data Analysis: A Survey
MULGONET: An interpretable neural network framework to integrate multi-omics data for cancer recurrence prediction and biomarker discovery
DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery
LGCDA: Predicting CircRNA-Disease Association Based on Fusion of Local and Global Features
Validating EmotiBit, an open-source multi-modal sensor for capturing research-grade physiological signals from anywhere on the body
Deep Imputation Bi-Stochastic Graph Regularized Matrix Factorization for Clustering Single-Cell RNA-Sequencing Data
Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma
Benchmarking of computational methods for predicting circRNA-disease associations
Introducing EmotiBit, an open-source multi-modal sensor for measuring research-grade physiological signals
Deep Reinforcement Learning for Online Resource Allocation in IoT Networks: Technology, Development, and Future Challenges
Balanced Contrastive Learning for Long-Tailed Visual Recognition
GANLDA: Graph attention network for lncRNA-disease associations prediction
KGANCDA: predicting circRNA-disease associations based on knowledge graph attention network
IGNSCDA: Predicting CircRNA-Disease Associations Based on Improved Graph Convolutional Network and Negative Sampling
HyPyP: a Hyperscanning Python Pipeline for inter-brain connectivity analysis
LDICDL: LncRNA-Disease Association Identification Based on Collaborative Deep Learning
CircR2Cancer: a manually curated database of associations between circRNAs and cancers
Survey of Network Embedding for Drug Analysis and Prediction
ILDMSF: Inferring Associations Between Long Non-Coding RNA and Disease Based on Multi-Similarity Fusion
Identifying miRNA‐disease association based on integrating miRNA topological similarity and functional similarity
Identification of protein complexes by integrating multiple alignment of protein interaction networks
Bioinformatics in protein kinases regulatory network and drug discovery
Interval-Based Similarity for Classifying Conserved RNA Secondary Structures
Exploring the effects of gene dosage on mandible shape in mice as a model for studying the genetic basis of natural variation