Nash Rochman Explores Host-Pathogen Interactions

Nash Rochman, PhD, Research Fellow/ Independent Research Scholar, Computational Biology Research Branch, NCBI

My research employs diverse computational approaches—from machine learning for image classification to epidemiological modelling in order to find unifying features of host-pathogen interactions, from viruses to cancer.

https://www.nlm.nih.gov/research/researchstaff/RochmanNash.html

Video transcript:

[Nash Rochman, PhD] There's a very old saying in physics that "it's great to be able to explain but it's better to predict". But it's also true that it's impossible to predict without an understanding, without an explanation.

If we're ever going to have a deeper understanding of of any biological system, for example, a relationship between a novel virus and a human host, we're going to need to have a deeper understanding of host-pathogen relationships with the information we have today.

So I study host-pathogen interactions and these could be human hosts and viral pathogens like SARS-Cov2. Host-pathogen relationships involve cancer in the host, or viruses in the host, or bacterial systems in the host. They could be animal hosts and bacterial pathogens. They could even be bacterial hosts and viral pathogens.

And I want to find unifying forces that shape the interactions between hosts and pathogens, to predict how the biology of the host can shape the evolution of the pathogen, and vice versa.
And this is important obviously for just understanding basic problems in biology.
But also, I think this is an interesting area because it provides immediate practical application as well.

Obviously, if you can find some forces that are shaping viral evolution, you might be able to use that information to help design better vaccines. If you find forces that are shaping bacterial evolution, in response to a virus, you might be able to find ways to better invent new antibiotics.

So, with more and more data, you can start predicting when the next pandemic will be or what the next pandemic will be. If you can predict, before it happens, you could even prevent the first human infection by mitigating the spread of that virus within the intermediate host population. And if you're really good, you can make that time negative. So you can mitigate it before it's ever isolated within a human host.

I want to help build a deeper understanding of well-conserved biological features - so that you can make longer timescale predictions, so you can better respond to biological rare events.

Видео Nash Rochman Explores Host-Pathogen Interactions канала National Library of Medicine