DML
DML Sharif University of Technology
CircWalk: Predicting CircRNA-Disease Associations using Graph Representation Learning
Description
Increasing evidence from novel research demonstrates that circRNAs play a role in the onset and development of various diseases. Recently, numerous computational methods have been proposed to predict circRNA-disease associations, as examining such associations merely by experimenting is too expensive and time-consuming to be feasible. In this work, we first discuss the theoretical foundations of searching for circRNA-disease associations. We then propose a method to construct a graph of circRNAs, diseases and other types of RNAs and map its entities to vectors, so as to use the said vectors to correctly label circRNA-disease pairs as either 'related' or 'unrelated'. Afterward, we compare our labels to the ground truth and evaluate our model in terms of prevailing evaluation metrics.
Dataset
Details
Start Date
Status
Feb. 20, 2022
100%
Contributors
Hamid R. Rabiee
Morteza Kouhsar
Esra Kashaninia
Collaborators
Dr. Mardani