Dear Colleagues,

Network medicine helps to provide insight into many chronic diseases by offering useful information about mechanistic information from omics data sets. Many diseases show different progression and different lethality in different ages and sexes. There are many different molecular processes that may be related to such aging processes that need to be elucidated. This elucidation is the first step in a personalized medicine approach. There are currently some different databases storing omics data related to aging (such as epigenetic data, methylation, as well as transcriptomic data annotated with patients’ age). Therefore, there is a need to introduce novel algorithms and models able to integrate and shed light on such processes.

This Special Issue aims to highlight novel research and applications in this area, coupled with representation learning and its implementations in biology, medicine, and pharmacology.

The Special Issue is focused on, but not limited to, the following broad areas:

• Network-based analysis in aging;
• Graph convolution neural networks;
• Network embedding in aging;
• Data integration;
• Drug discovery through network medicine in aging.

Prof. Dr. Pietro Hiram Guzzi
Dr. Gaia C. Mannino
Dr. Francesco Petrizzelli
Dr. Elisabetta Pedace
Guest Editors

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• ageing network analysis
• artificialel intelligence