Area of research
Computational Theory and Mathematics · Molecular Biology
Research interest
Research focused on Drug and Computational biology, with related work in Drug repositioning, Docking (animal), Similarity (geometry). Notable publications include 'Drug repositioning by applying ‘expression profiles’ generated by integrating chemical structure similarity and gene semantic similarity', 'Synthetic Lethality-based Identification of Targets for Anticancer Drugs in the Human Signaling Network', and 'Identification of long-term survival-associated gene in breast cancer'.
Integrating Hypoxia Signatures from scRNA-seq and Bulk Transcriptomes for Prognosis Prediction and Precision Therapy in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma
Predicting drug synergy using a network propagation inspired machine learning framework
Identifying a survival-associated cell type based on multi-level transcriptome analysis in idiopathic pulmonary fibrosis
Identification of Warning Transition Points from Hepatitis B to Hepatocellular Carcinoma Based on Mutation Accumulation for the Early Diagnosis and Potential Drug Treatment of HBV‐HCC
Exploring Precise Medication Strategies for OSCC Based on Single-Cell Transcriptome Analysis from a Dynamic Perspective
Identification of long-term survival-associated gene in breast cancer
Computational drug repositioning based on the relationships between substructure–indication
Synthetic Lethality-based Identification of Targets for Anticancer Drugs in the Human Signaling Network
Designing of dual inhibitors for GSK-3β and CDK5: Virtual screening and<i>in vitro</i>biological activities study
Prediction on the risk population of idiosyncratic adverse reactions based on molecular docking with mutant proteins
Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
In silico drug repositioning for the treatment of Alzheimer's disease using molecular docking and gene expression data
Drug repositioning by applying ‘expression profiles’ generated by integrating chemical structure similarity and gene semantic similarity