Quantifying Mutational Response to Track the Evolution of SARS-CoV-2 Spike Variants: Introducing a Statistical-Mechanics-Guided Machine Learning Method


Journal article


Satyam Sangeet, Raju Sarkar, Saswat K. Mohanty, Susmita Roy*
Journal of Physical Chemistry B, vol. 126(40), ACS Publications, 2022, pp. 7895-7905


Cite

Cite

APA
Sangeet, S., Sarkar, R., Mohanty, S. K., & Roy*, S. (2022). Quantifying Mutational Response to Track the Evolution of SARS-CoV-2 Spike Variants: Introducing a Statistical-Mechanics-Guided Machine Learning Method. Journal of Physical Chemistry B, 126(40), 7895–7905.

Chicago/Turabian
Sangeet, Satyam, Raju Sarkar, Saswat K. Mohanty, and Susmita Roy*. “Quantifying Mutational Response to Track the Evolution of SARS-CoV-2 Spike Variants: Introducing a Statistical-Mechanics-Guided Machine Learning Method.” Journal of Physical Chemistry B 126, no. 40 (2022): 7895–7905.

MLA
Sangeet, Satyam, et al. “Quantifying Mutational Response to Track the Evolution of SARS-CoV-2 Spike Variants: Introducing a Statistical-Mechanics-Guided Machine Learning Method.” Journal of Physical Chemistry B, vol. 126, no. 40, ACS Publications, 2022, pp. 7895–905.