Deep learning algorithms for predicting tandem mass spectra of peptides
Previously, we have developed a deep learning algorithm PredFull for predicting the full tandem mass spectra of peptides without modifications. In this project, we attempt to investigate if the deep learning methods can be extended to spectra prediction for peptides containing post-translation modifications (PTMs). The project will involve the assembly large training datasets of mass spectra and the training of deep neural networks using these data.
Department: Computer Science
Supervising Faculty: Haixu Tang
No need to have prior experiences in machine learning, but some experience in python programming will be helpful.
Team meetings will be online
Conditions of Employment
Other pay information: course credit or paid
Expected Hours Per Week: 0
For more information, contact: Prof. Haixu Tang (email@example.com). To apply, send Yuzhen a short email with why you are interested in the project and a brief introduction of yourself.