Society for Mathematical Biology - Subgroups

The Subgroup on Cell and Developmental Biology brings together researchers who are interested in understanding cell and developmental biology phenomena using quantitative approaches. Cell and developmental biology has long proven a fertile ground for mathematical modelling and, with recent advances in microscopy, image analysis, and fluorescent reporter methods, it is becoming an increasingly quantitative discipline. We are now able to constrain mathematical models of developmental processes, for example through parameter estimation, increasing the potential of such models to be used in a predictive way. The objective of this Subgroup is to accelerate these efforts, by supporting and advancing the use of mathematical modelling as part of the ‘toolkit’ of cell and developmental biology.

Chair: Andreas Buttenschoen, abuttens@math.ubc.ca

Secretary: Alexander Fletcher, a.g.fletcher@sheffield.ac.uk

Committee Members: Ruth Baker, Linus Schumacher, and Michael Watson

The Education Subgroup of SMB is comprised of members who desire to improve the teaching and mentoring of future scientists, and in particular undergraduate and graduate mathematical and computational biology researchers. As new research frontiers emerge, our members seek to understand the best practices to help future researchers of biological questions be successful in this space. Content areas include, but are not limited to the teaching and learning of modeling, computing, data science, and quantitative reasoning. Challenge spaces include, but are not limited to designing learning experiences across disciplines, defining and assessing outcomes for new interdisciplinary and technological spaces, integrating data with mathematical modeling, educational outreach initiatives, and providing an inclusive and diverse environment for learning and for the profession. Chair: Dr. Holly Gaff, HGafff@odu.edu Past Chair: Carrie Diaz Eaton, cdeaton@bates.edu Twitter: @Edu4SMB

The Immunobiology and Infection Subgroup brings together researchers who are interested in the modeling and analysis of immune processes in human disease and of host-pathogen interactions. Our members study various topics, including within-host infectious disease dynamics, host immune responses, causes and effects of inflammation, disease progression and outcome, integration of experimental and clinical data into models, and model-driven experimental design.

Chair: Angela Reynolds, areynolds2@vcu.edu

Secretary/Treasurer: Jonathan Forde

Advisory Committee Members: Jessica Conway and Stanca Ciupe

Twitter: @smb_imin

The Mathematical Epidemiology Subgroup brings together scholars interested in dynamical modeling and statistical analysis of the spread of infectious diseases. Topics of interest to the group include: deterministic and stochastic modelling of population dynamics of infectious diseases; statistical analysis of population-level infectious disease data; describing and modelling human behavioral decisions in relation to infectious diseases; control and eradication strategies for endemic infections; prevention and response strategies for emerging and re-emerging infections; effects of antimicrobial resistance; policy implications.

Chairs: Zhilan Feng fengz@purdue.edu

Twitter: #SMBMathEpi

The Mathematical Neuroscience Subgroup provides a forum for the use and development of advanced mathematical techniques in the modelling and analysis in all areas of neuroscience – from cells to networks. The frameworks of Dynamical Systems, Network Science, Scientific Computation, Information theory, and Stochastic processes are just a few areas that we are using to advance knowledge on synaptic plasticity, neural rhythm generation, memory and learning, decision making, and natural computation, hand-in-hand with colleagues from experimental and clinical neuroscience.

Chairs: Cheng Ly, cly@vcu.edu; Wilten Nicola, wilten.nicola@ucalgary.ca

Email: mathneurocollective@gmail.com

Twitter: @MathNeuro_

The Mathematical Oncology Subgroup is focused on integrating and applying mathematical and computational models to better understand and predict cancer initiation, progression, and treatment. Chairs: Alexander R. A. Anderson, Alexander.Anderson@moffitt.org; Heiko Enderling, Heiko.Enderling@moffitt.org

Twitter: @mathonco

Website: http://mathematical-oncology.org

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, kbflores@ncsu.edu; Erica Rutter, erutter2@ucmerced.edu; John Nardini, jtnardin@ncsu.edu

Twitter: @SMBmfbm

The Population Dynamics, Ecology and Evolution Subgroup aims to foster a discussion on theoretical, mathematical and empirical approaches to core topics in population dynamics, ecology and evolution.

Chair: R. Christina Cobbold, Christina.Cobbold@glasgow.ac.uk

Secretary: James Watmough, watmough@unb.ca

Twitter: @smbpdee

Google Group: smbpdee