Research
Machine learning for the microbiome
Uppal, G., et al. (2024). MCSPACE: inferring microbiome spatiotemporal dynamics from high-throughput co-localization data. bioRxiv: the preprint server for biology.
Uppal, G. & Gerber, G. K. (2023). MC-SPACE: Microbial communities from spatially associated counts engine. ICML CompBio.
MCSPACE software package available here
Physics of microbial evolution and engineering microbial interactions
Uppal, G. and Vural, D.C., 2024. On the possibility of engineering social evolution in microfluidic environments. Biophysical Journal, 123(3), pp.407-419.
Uppal, G., Hu, W. and Vural, D.C., 2020. Evolution of chemotactic hitchhiking. Journal of evolutionary biology, 33(11), pp.1593-1605.
Uppal, G. and Vural, D.C., 2020. Evolution of specialized microbial cooperation in dynamic fluids. Journal of evolutionary biology, 33(3), pp.256-269.
Uppal, G. and Vural, D.C., 2018. Shearing in flow environment promotes evolution of social behavior in microbial populations. Elife, 7, p.e34862.
Physics of aging
- Uppal, G., Bahcecioglu, G., Zorlutuna, P. and Vural, D.C., 2020. Tissue failure propagation as mediated by circulatory flow. Biophysical Journal, 119(12), pp.2573-2583.
Quantum transport and themoelectic efficiency
- Monteros, A.L., Uppal, G.S., McMillan, S.R., Crisan, M. and Ţifrea, I., 2014. Thermoelectric transport properties of a T-shaped double quantum dot system in the Coulomb blockade regime. The European Physical Journal B, 87, pp.1-6.