Area of research
Cancer Research · Computational Theory and Mathematics
Research interest
Research interests include MicroRNA in disease regulation, Computational Drug Discovery Methods, Circular RNAs in diseases, and Cancer-related molecular mechanisms research.
Deciphering the pharmacological mechanisms of Weiweisu decoction in chronic atrophic gastritis: Insights from network pharmacology, molecular dynamics, and in vivo validation
Group decision on rationalizing disease analysis using novel distance measure on Pythagorean fuzziness
Therapeutic efficacy of ECs Foxp1 targeting Hif1α-Hk2 glycolysis signal to restrict angiogenesis
Identification and Functional Analysis of circRNAs during Goat Follicular Development
Review of machine learning and deep learning models for toxicity prediction.
Biotransformation of bisphenol A in vivo and in vitro by laccase-producing Trametes hirsuta La-7: Kinetics, products, and mechanisms
Machine learning and deep learning for brain tumor MRI image segmentation.
Three-Dimensional Structural Insights Have Revealed the Distinct Binding Interactions of Agonists, Partial Agonists, and Antagonists with the µ Opioid Receptor.
Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment.
Exosome-shuttled miR-126 mediates ethanol-induced disruption of neural crest cell-placode cell interaction by targeting SDF1
Analyzing 3D structures of the SARS-CoV-2 main protease reveals structural features of ligand binding for COVID-19 drug discovery.
Machine Learning Models for Predicting Cytotoxicity of Nanomaterials.
The novel importance of miR-143 in obesity regulation
Dexamethasone and potassium canrenoate alleviate hyperalgesia by competitively regulating IL‐6/JAK2/STAT3 signaling pathway during inflammatory pain in vivo and in vitro
Deep Learning Models for Predicting Gas Adsorption Capacity of Nanomaterials.
Free energy perturbation–based large-scale virtual screening for effective drug discovery against COVID-19
Machine learning models for rat multigeneration reproductive toxicity prediction.
Machine learning driven by environmental covariates to estimate high-resolution PM2.5 in data-poor regions
Machine Learning Models for Predicting Liver Toxicity.
Rhodiola pre-conditioning reduces exhaustive exercise-induced myocardial injury of insulin resistant mice
The Emerging Role of BDNF/TrkB Signaling in Cardiovascular Diseases
Nanomaterial Databases: Data Sources for Promoting Design and Risk Assessment of Nanomaterials.
Advances in cell death - related signaling pathways in acute-on-chronic liver failure
Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations.
Identification of Epidemiological Traits by Analysis of SARS-CoV-2 Sequences.
Identification of key miRNA signature and pathways involved in multiple myeloma by integrated bioinformatics analysis
MiR-125b-2 knockout increases high-fat diet-induced fat accumulation and insulin resistance
Displacement of peritoneal end of a shunt tube to pleural cavity: A case report
MicroRNA-365 suppressed cell proliferation and migration via targeting PAX6 in glioblastoma.
PubMed 2019cited by 14position: middle
Selection of reference genes for miRNA quantitative PCR and its application in miR-34a/Sirtuin-1 mediated energy metabolism in Megalobrama amblycephala