1 citations · 1 across the 3 of their papers we have counts for
3 papers
Using PyBioNetFit to Leverage Qualitative and Quantitative Data in Biological Model Parameterization and Uncertainty Quantification
Ely F. Miller, Abhishek Mallela, Jacob Neumann +3
Data generated in studies of cellular regulatory systems are often qualitative. For example, measurements of signaling readouts in the presence and absence of mutations may reveal…
Data-Driven Modeling of Dislocation Mobility from Atomistics using Physics-Informed Machine Learning
Yifeng Tian, Soumendu Bagchi, Liam Myhill +5
Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic def…
Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit
Jacob Neumann, Yen Ting Lin, Abhishek Mallela +6
Bayesian inference in biological modeling commonly relies on Markov chain Monte Carlo (MCMC) sampling of a multidimensional and non-Gaussian posterior distribution that is not anal…