Di Meng

Graduate

Keywords

Project Title

Predicting intrinsically disordered regions in proteins by Deep Learning

Project Description

Intrinsically Disordered Proteins and Regions (IDPs/IDRs) are critical to various protein functions and are implicated in numerous diseases. However, their inherent flexibility and the scarcity of high-quality datasets present significant challenges in accurately predicting their structure and function. This project initially focuses on the general prediction of IDRs, followed by a specific identification of functional disordered regions, Disordered Flexible Linkers. Ultimately, the project aims to advance to the prediction of protein regions associated with amyloid-related diseases.