Area of research
Molecular Biology · Organic Chemistry
Research interest
Research interests include Advanced biosensing and bioanalysis techniques, RNA Interference and Gene Delivery, Carbohydrate Chemistry and Synthesis, and Glycosylation and Glycoproteins Research.
SMAD2 S-palmitoylation promotes its linker region phosphorylation and T <sub>H</sub> 17 cell differentiation in a mouse model of multiple sclerosis
NLRP3 Cys126 palmitoylation by ZDHHC7 promotes inflammasome activation
Sirt2 inhibition improves gut epithelial barrier integrity and protects mice from colitis
Binding Affinity Determines Substrate Specificity and Enables Discovery of Substrates for N-Myristoyltransferases
High-Throughput Enzyme Assay for Screening Inhibitors of the ZDHHC3/7/20 Acyltransferases
Sirtuin 3 Inhibition Targets AML Stem Cells through Perturbation of Fatty Acid Oxidation
A STAT3 palmitoylation cycle promotes TH17 differentiation and colitis
NMT1 and NMT2 are lysine myristoyltransferases regulating the ARF6 GTPase cycle
An improved 4′-aminomethyltrioxsalen-based nucleic acid crosslinker for biotinylation of double-stranded DNA or RNA
A Small‐Molecule SIRT2 Inhibitor That Promotes K‐Ras4a Lysine Fatty‐Acylation
Direct Comparison of SIRT2 Inhibitors: Potency, Specificity, Activity‐Dependent Inhibition, and On‐Target Anticancer Activities
High throughput mass spectrometry-based characterisation of <i>Arabidopsis thaliana</i> group H glycosyltransferases
Collaborative Research: Design-Based Optimal Subdata Selection Using Mixture-of-Experts Models to Account for Big Data Heterogeneity
Collaborative Research: Information-Based Subdata Selection Inspired by Optimal Design of Experiments
Collaborative research: A major leap forward: Optimal designs for correlated data, multiple objectives, and multiple covariates
CAREER: Optimal Design of Experiments for Generalized Linear Models
CAREER: Optimal Design of Experiments for Generalized Linear Models
Collaborative Research: Optimal Design of Experiments for Categorical Data
Crossover Designs for Comparing Test Treatments with a Control Treatment: Optimality, Efficiency, and Robustness
Crossover Designs for Comparing Test Treatments with a Control Treatment: Optimality, Efficiency, and Robustness