Research
Our research focuses on developing bioinformatic tools using artificial intelligence, machine learning, data analysis, statistical physics, stochastic modelling and quantum chemistry.
Current Research Projects
Below are our main research areas and ongoing projects.
Prediction of B-cell Epitopes for Vaccine Design
Our lab develops computational methods for predicting B-cell epitopes, which are crucial for rational vaccine design and antibody engineering. This research contributes to the development of more effective vaccines and therapeutic antibodies.
Read more →Prediction of Disease-Causing Variants in the Human Genome
We develop computational tools to predict the pathogenicity of genetic variants, helping to identify disease-causing mutations in the human genome. This research has important implications for personalized medicine and genetic counseling.
Read more →Rational Design of Modified Proteins
Our research focuses on the rational design of proteins with modified properties, utilizing computational methods to predict and optimize protein stability, solubility, and binding affinity. This work has applications in biotechnology, drug design, and industrial enzyme engineering.
Read more →Study of Dynamics of House Dust Mite Allergens from Family 5
Our research investigates the structural dynamics and biophysical properties of house dust mite allergens using computational approaches. This work contributes to understanding allergic mechanisms and developing better diagnostic and therapeutic strategies.
Read more →Synthetic Gene Circuits and Noise Control
We use stochastic modeling to study synthetic gene circuits and develop strategies for controlling biological noise. This research has applications in synthetic biology and understanding fundamental principles of gene regulation.
Read more →