Members
M.S. Students
Seungwoo Baek (백승우)
B.S. in Internet of Things
Host-pathogen protein-protein interaction prediction
Protein-protein interactions (PPIs) between hosts and pathogens play an important role in the process of infectious disease. By identifying host-pathogen PPIs, it is possible to identify disease pathways or accelerate the development of therapeutic approaches. I am interested in applying protein language models to predict PPIs.
Daehun Bae (배대훈)
B.S. in Chemistry
Antimicrobial Peptide Activity Prediction
Antibiotics were designed to kill the bacteria. But, abuse of antibiotics, Antimicrobial resistance (AMR) has become more critical problem in treatment. So we need to find new antimicrobial agents. Antimicrobial Peptides (AMPs) are considered as best substitute of antibiotics. AMPs are small size of polypeptides and key component of the biological innate immune system. I'm studying about AMP activity prediction with deep learning methods.
Chihyeon Jin (진치현)
B.S. in Computer Science and Engineering
Multi-target compound generation
Multi-target drugs can act on different targets simultaneously. With this ability, multi-target drugs have several advantages, such as increased drug resistance and reduced drug-drug interaction. The deep learning based generative model can help to design multi-target compounds. I am interested in applying deep learning methods to multi-target compound generation.
Juntae Park (박준태)
B.S. in Electrical Engineering
With the growing threat of antibiotic-resistant bacteria, we need antimicrobial peptides with more novel and desired properties. Antimicrobial peptides(AMPs) are small peptides of 10-50 amino acids that kill bacteria by inhibiting their activity or penetrating cell membranes. However, producing and identifying AMPs is time consuming and expensive. Therefore, I am interested in using deep learning to generate AMPs with desired properties.
