Fast, flexible tools to map how viruses like SARS-CoV-2 spread

Fast and flexible Bayesian phylogenetics via modern machine learning

NIH-funded research Fred Hutchinson Cancer Center · NIH-11099997

This project builds fast computer methods that use thousands of viral genomes to track how the coronavirus spreads and support public health response.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionFred Hutchinson Cancer Center NIH-funded
Lab location1 site (Seattle, United States)
Project IDNIH-11099997 on NIH RePORTER

What this research studies

From a patient perspective, researchers are creating new machine-learning versions of Bayesian phylogenetics so they can analyze thousands of viral genomes quickly and with reliable uncertainty estimates. They'll develop mathematical tools and fast algorithms (including online updates and convergence checks) and implement them in popular frameworks like TensorFlow and PyTorch. The methods will let scientists combine genome sequences with data such as sampling location and migration patterns to produce clearer pictures of how outbreaks move. Those improved maps are intended to inform strategies for controlling viral spread.

Who could benefit from this research

Good fit: People with confirmed SARS-CoV-2 infection whose viral samples are sequenced and shared in public or research databases are the individuals whose data could be included.

Not a fit: Patients without viral genome sequencing or people with conditions unrelated to viral infections would not directly benefit from this computational work.

Why it matters

Potential benefit: If successful, this work could give public health teams faster and clearer information about outbreak spread, helping reduce infections and target interventions sooner.

How similar studies have performed: Traditional phylogenetic and genomic-tracing methods have helped map outbreaks, but applying scalable variational machine-learning methods to thousands of genomes is a newer and less-tested approach.

Where this research is happening

Seattle, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.