Math Bio Seminar

Speaker: 
Iman Dehzangi
Topic: 
Dr. Iman Dehzangi, Rutgers University, Camden

Abstract:

Machine Learning (ML) and Deep Learning (DL) have emerged as powerful tools in addressing complex issues within Bioinformatics and Computational Biology, offering promising alternatives to traditional experimental and computational methodologies. At the Machine Learning, Bioinformatics, and Computational Biology (MLBC) lab at Center for Computational and Integrative Biology (CCIB) at Rutgers University, Camden, we are dedicated to tackling a wide range of challenging problems. These include predicting protein folding, structural classification, subcellular localization, and post-translational modifications (PTMs), alongside problems in biomedical image processing, cancer detection, and cancer subtype identification. Our approach involves leveraging various classification techniques, with an emphasis on deep learning architectures trained on novel features extracted from evolutionary and structural properties of proteins and genes. In this presentation, I will discuss both past and ongoing research aimed at constructing integrated models to tackle these challenges, while also outlining future directions for solving these crucial issues.

Event Date: 
April 1, 2024 - 3:30pm to 4:30pm
Location: 
105 MLH or Online (See URL)
Calendar Category: 
Seminar
Seminar Category: 
Mathematical Biology