Modeling the generation of somatic mosaicism in the brain
Collaborators: M. McConnell, Fred Gage, Jerold Chun, and Jan Medlock

Briefly, according to a selection of basic branching process model assumptions, we randomly generate an ensemble of NS/PC lineage trees, such as the tree pictured. Overall, we impose that the computed ensembles of trees are consistent with population-averaged data on neuron production in the mouse. This provides a quantitative framework for addressing outstanding questions concerning variability in NS/PC daughter cell fate decision making. Also, these models provide a means for quantifying how this variability relates to the generation and composition of the neural genomic mosaic. Preliminary exploration of qualitative model behaviors within our computational framework has provided testable hypotheses and identified key experiments moving forward.
The biology of neurogenesis provides rich in vivo context for moving beyond the average cell perspective to develop a middle-out approach to modeling cell biological systems. With population-level data as constraints, we ultimately seek to incorporate simplified single-cell models and build explanatory models for the molecular basis of single-cell variability. Doing so will be necessary to understand how genetic alterations causally linked to a specific neurological disease actually cause the pathological cell loss or cell damage characteristic of the disease.
- H. R. MacMillan and M. J. McConnell, 2010. "Seeing beyond the average cell: Branching process models of cell proliferation, differentiation, and death during mouse brain development. Theory in Biosciences, Submitted, Oct. 2009.
- M. J. McConnell, H. R. MacMillan, and J. Chun, 2009. "Mathematical modeling supports substantial neural progenitor cell death." Neural Development. 4(28): 1-12. doi:10.1186/1749-8104-4-28. Link
- M. A. Case, H. R. MacMillan, 2009. "On simulating the generation of mosaicism during mammalian cerebral cortical development." Journal of Biological Systems. 17(1): 27-62. doi:10.1142/S0218339009002740. Link. PDF.
Biogeochemistry of constructed wetlands for water remediation
Collaborators: Brandon Pelfrey, Scott Brame, John Rodgers, and James Castle.

As a consequence, wetlands designed to facilitate the microbial-mediated reduction of SeVI and SeIV hold promise as a sustainable means of treating agricultural, municipal, and industrial waters high in selenium. Toward the optimal design of such constructed wetlands, we are developing multiscale, multiphase, and multispecies mathematical models of selenium transport and fate to better understand the processes of advection, diffusion, reaction, volatilization, and biotransformation of selenium in free-surface wetlands densely buffered with typha latifolia (i.e., ``cat tails''). In particular, our models incorporate the effects of wetland architecture, plant buffering and litter, biofilm structure and composition, redox potential (eH), hydrogen ion activity (pH), soluble oxygen, temperature, and environmental perturbations.
- B. Pelfrey, S. Brame, H.R. MacMillan, J. Castle, and J. Rodgers, 2010. "Modeling microbial-mediated reduction of selenium in pilot-scale constructed wetlands." In preparation.
Reduced-order models of the cellular response to DNA damage
Collaborators: Mike McConnell.

- H.R. MacMillan and M. J. McConnell, 2010. "A nest of qualitative DNA damage response networks." In preparation.
Meshfree least squares methods
Collaborators: Max Gunzburger and John Burkardt
Convergence is established for a meshfree first-order system least squares (FOSLS) partition of unity (PU) finite element method. By virtue of the partition of unity, local approximation gives rise to global approximation in H(div)&cap H(curl) . FOSLS provides local a posteriori error estimation to guide the judicious allotment of new degrees of freedom when adaptively enriching an initially-coarse point set used to construct a meshfree discretization. Hence, this synthesis can be used to leverage the advantages of meshfree approach. Beyond mechanics and classical PDE systems, application of PU methods to dynamic cell-centered biological simulations may hold special promise. This is due to natural interest in either moving (cell migration), eliminating (cell death), or adding (cell division) subsets of points used to build multilevel---with respect to biological organization---descriptions of various molecular factors and their impact on cell fate decisions.
- H.R. MacMillan, M. D. Gunzburger, and J. D. Burkardt, 2007. "Meshfree First-order System Least Squares." Numerical Mathematics: Theory, Methods, and Applications. 1:29-43. Link.
Acetylcholine Reaction and Diffusion within a Neuromuscular Junction
Collaborators: Kaihsu Tai, Steve Bond, Nathan Baker, Andy McCammon, and Michael Holst.

- K. Tai, S. D. Bond, H. R. MacMillan, N. A. Baker, M. J. Holst and J. A. McCammon, 2003. "Finite Element Simulations of Acetylcholine Diffusion in Neuromuscular Junctions." Biophysical Journal. 84:2234-2241. Link.
First-order system least squares for and electrical impedance tomography
Collaborators: T. A. Manteuffel and Stephen F. McCormick.

- H. R. MacMillan, T. A. Manteuffel, and S. F. McCormick, 2004. "First-order system least squares and electrical impedance tomography," SIAM Journal of Numerical Analysis, 42(2): 461-483. Link.
- H. R. MacMillan, 2001. "First-order system least squares and electrical impedance tomography." Dept. of Applied Mathematics, Univ. of Colorado at Boulder, Ph.D. Thesis. Link.
Stability of a pair of vortex filaments
Collaborators: A. Majda and R. McLaughlin.

- H. R. MacMillan, 1994. "The stability of a pair of vortex filaments." Thesis No. 4873, Princeton University. Link &minus (search author = MacMillan)