3 papers
q-bio.QM2025
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…
q-bio.QM2021
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…
q-bio.PE2020
Daily Forecasting of New Cases for Regional Epidemics of Coronavirus Disease 2019 with Bayesian Uncertainty Quantification
Yen Ting Lin, Jacob Neumann, Ely Miller +7
To increase situational awareness and support evidence-based policy-making, we formulated two types of mathematical models for COVID-19 transmission within a regional population. O…