Charles J. Mode
Affiliations: | Drexel University, Philadelphia, PA, United States |
Area:
Biostatistics Biology, Statistics, Public HealthGoogle:
"Charles Mode"Cross-listing: PHTree
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Publications
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| Mode CJ. (2020) An Algorithmic Approach to Modelling the Co-Evolution of Parasites and Their Hosts International Journal of Statistics and Probability. 9: 13 |
| Mode CJ, Sleeman CK. (2019) A Review of the Methodologies Used in the Derivation of Formulas for Parametric Survival Functions with Illustrative Numerical Examples International Journal of Statistics and Probability. 8: 99 |
| Mode CJ, Sleeman CK, Raj T. (2013) On the inclusion of self regulating branching processes in the working paradigm of evolutionary and population genetics. Frontiers in Genetics. 4: 11 |
| Mode CJ, Sleeman CK, Raj T. (2013) Simulating the emergence of mutations and their subsequent evolution in an age-structured stochastic self-regulating process with two sexes International Journal of Stochastic Analysis. 2013 |
| Mode CJ, Durrett R, Klebaner F, et al. (2013) Applications of stochastic processes in biology and medicine International Journal of Stochastic Analysis. 2013 |
| Nishiura H, Yan P, Sleeman CK, et al. (2012) Estimating the transmission potential of supercritical processes based on the final size distribution of minor outbreaks. Journal of Theoretical Biology. 294: 48-55 |
| Mode CJ, Raj T, Sleeman CK. (2011) Simulating the emergence and survival of mutations using a self regulating multitype branching processes Journal of Probability and Statistics |
| Mode CJ, Gallop RJ. (2008) A review on Monte Carlo simulation methods as they apply to mutation and selection as formulated in Wright-Fisher models of evolutionary genetics. Mathematical Biosciences. 211: 205-25 |
| Gallop RJ, Mode CJ, Sleeman CK. (2006) A stochastic model incorporating HIV treatments for a heterosexual population: Impact on threshold conditions Biomathematics: Modelling and Simulation. 59-84 |
| Gallop RJ, Mode CJ, Blank K, et al. (2005) Application of a Mixed Effects Model for Biosurveilliance of Regional Rail Systems Journal of Data Science. 3: 353-370 |