Effector-GAN: prediction of fungal effector proteins based on pretrained deep representation learning methods and generative adversarial networks.
Journal:
Bioinformatics (Oxford, England)
PMID:
35640972
Abstract
MOTIVATION: Phytopathogenic fungi secrete effector proteins to subvert host defenses and facilitate infection. Systematic analysis and prediction of candidate fungal effector proteins are crucial for experimental validation and biological control of plant disease. However, two problems are still considered intractable to be solved in fungal effector prediction: one is the high-level diversity in effector sequences that increases the difficulty of protein feature learning, and the other is the class imbalance between effector and non-effector samples in the training dataset.