disease gene prediction

A comprehensive overview of fundamental concepts, deep learning methods and critical challenges of Network Biology in Network Biology, Network Medicine, and Network Pharmacology.

A comprehensive overview of fundamental concepts, deep learning methods and critical challenges of Network Biology in Network Biology, Network Medicine, and Network Pharmacology.

Authored a chapter in the textbook Deep Learning in Biology and Medicine. In the chapter we introduced the fundamental concepts of Network Biology, and we presented the state-of-the-art deep learning strategies used to tackle critical challenges in Network Biology, Network Medicine, and Network Pharmacology.

Developed a deep graph learning-based model for predicting disease-gene associations. The model jointly learns functional and connectivity patterns using a novel technique based on attributed random walks.

Developed a deep graph learning model for predicting disease-gene associations. The model jointly learns functional and connectivity patterns using a novel technique based on attributed random walks.

A novel graph deep learning model for predicting disease-gene associations. The model jointly learns functional and connectivity patterns using a novel technique based on attributed random walks.

A novel graph deep learning model for predicting disease-gene associations. The model jointly learns functional and connectivity patterns using a novel technique based on attributed random walks. (Conference version)

A presentation about the current research projects of the lab. As research project for the “AI for Health and Medicine” workshop, I presented the first version of RW², a novel graph deep learning model for predicting disease-gene associations.