The current pandemic has highlighted the need for methodologies that can quickly and reliably prioritize clinically approved compounds for their potential effectiveness for SARS-CoV-2 infections. In the past decade, network medicine has developed and validated multiple predictive algorithms for drug repurposing, exploiting the sub-cellular network-based relationship between a drug's targets and disease genes. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity, tasking each of them to rank 6,340 drugs for their expected efficacy against SARS-CoV-2.
The lecture will be delivered by Deisy Morselli Gysi, Ph.D., Postdoctoral Research Associate at the Center for Complex Network Research. Dr. Gysi’s research has mostly focused on biomarker discovery and drug repurposing, mostly using a multi-omic machine learning and network analysis approach. She has developed methods for the construction and comparison of co-expression networks in the past, and now she focuses on biomarker discovery and drug repurposing for autoimmune diseases and viral infections, such as COVID-19.
You may indicate your interest in attending this online lecture at: https://neu.co1.qualtrics.com/jfe/form/SV_beVgqiTaBsp0b5P.
Date and Time:
Thursday, October 22, 2020, 12:00 – 1:00 pm ET
Join Zoom Meeting:
Meeting ID: 941 2638 5015
Dial by your location: +1 312 626 6799 (US)
Find your local number: https://northeastern.zoom.us/u/aFiXRktMe
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