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Ken Agbo

PhD Student

Edith Cowan University

Ken’s research interest hovers in the application of machine learning for bioactive peptides discovery. His present research focuses on the development of machine learning-based tools for in-silico screening of antioxidant, antihypertensive, anticancer, and antimicrobial bioactive peptides. He identifies bioactive peptides from mungbean, chickpeas, wheat, and oats using mass spectrometry-based proteomics approaches and uses his developed models to screen the peptides for their bioctivities. Ken also carries out in vitro screening of the potential peptides to test his developed tools.