Machine Learning Models for Predicting Antimicrobial Peptides
Zhanshuo Tong
Undergraduate Researcher
Informatics Major (Luddy School of Informatics, Computing, & Engineering)
Haixu Tang
Faculty Mentor
Haixu Tang (Luddy School of Informatics, Computing and Engineering)
Project Description
Antibiotic resistance occurs when germs like bacteria develop the ability to escape the antibiotic drugs, which impose a challenge to design a large variety of antibiotic molecules. Antimicrobial peptides are often used by organisms like fungi and plants to kill bacterial. In this project, we hope to develop machine learning models for predicting the antibiotic potential of peptides. In a long term, we also want to develop a generative learning model that can generate novel antimicrobial peptides.
Technology or Computational Component
Develop predictive and generative machine learning models using the deep learning framework.