Methods for Biological Modeling

The Methods for Biological Modeling Subgroup brings together those interested in the development of novel application of methods (e.g., numerical, analytical/theoretical, agent-based modeling, statistical, parameter estimation, identifiability, and machine learning) towards modeling biological systems. In applying standard methodologies, mathematical modelers encounter many challenges with simulating and analyzing biological systems, such as high dimensionality, computational complexity, observation or process error, model bias, and intra- and inter-individual heterogeneity. The objective of the Subgroup is to support and disseminate new advances in tackling these challenges to the Mathematical Biology community.

Chairs:
Kevin Flores, North Carolina State University
kbflores@ncsu.edu

Erica Rutter, University of California Merced
erutter2@ucmerced.edu

John Nardini, The College of New Jersey
nardinij@tcnj.edu

Social Media:
Twitter: @SMBmfbm

Website: https://methods-biomodeling.org/