Research
UC San Diego / San Diego Supercomputer Center · May 2024 – Dec 2025
Metabolomics-Based ML Diagnostics of PASC
- ML diagnosis of Long COVID from metabolomic data
- Molecular descriptors make it work across lab assays
- Distinguishes Long COVID from 4 of 5 similar diseases
About
Machine learning pipeline for diagnosing Post-Acute Sequelae of SARS-CoV-2 Infection (Long COVID) using metabolomic data. A proof of concept that molecular descriptors calculated using E-Dragon can work to build assay-agnostic diagnostic algorithms with disease differentiating power. Differentiates PASC from 4 of the 5 PASC-similar diseases tested (ME/CFS, Lyme disease, POTS, and IBS), with only fibromyalgia proving indistinguishable. First-author paper published in Metabolites.
- Python
- Machine Learning
- Bioinformatics