Mathematical Modelling with Multidisciplinary Applications (M3A)
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Modified Hamiltonian Monte Carlo for Bayesian Inference
(Statistics and Computing, 20190722)The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computational statistics. We show that performance of HMC can be significantly improved by incorporating importance sampling and ... 
Opportunities at the Intersection of Synthetic Biology, Machine Learning, and Automation
(ACS Synthetic Biology, 201907)Our inability to predict the behavior of biological systems severely hampers progress in bioengineering and biomedical applications. We cannot predict the effect of genotype changes on phenotype, nor extrapolate the ... 
A concerted systems biology analysis of phenol metabolism in Rhodococcus opacus PD630
(Metabolic Engineering, 201906)Rhodococcus opacus PD630 metabolizes aromatic substrates and naturally produces branchedchain lipids, which are advantageous traits for lignin valorization. To provide insights into its lignocellulose hydrolysate utilization, ... 
ConductanceBased Refractory Density Approach for a Population of Bursting Neurons
(Bulletin of Mathematical Biology, 2019)The conductancebased refractory density (CBRD) approach is a parsimonious mathematicalcomputational framework for modeling interact ing populations of regular spiking neurons, which, however, has not been yet extended ... 
Exploring Liion conductivity in cubic, tetragonal and mixedphase Alsubstituted Li7La3Zr2O12 using atomistic simulations and effective medium theory
(Acta Materialia, 20190815)Garnet Li7La3Zr2O12 (LLZO) is a promising solid electrolyte candidate for solidstate Liion batteries, but at room temperature it crystallizes in a poorly Liion conductive tetragonal phase. To this end, partial substitution ... 
Brain energetics plays a key role in the coordination of electrophysiology, metabolism and hemodynamics: evidence from an integrated computational model
(Journal of theoretical biology, 20190605)The energetic needs of brain cells at rest and during elevated neuronal activation has been the topic of many investigations where mathematical models have played a significant role providing a context for the interpretation ... 
Patientspecific modelling of cortical spreading depression applied to migraine studies
(20190617)Migraine is a common neurological disorder and onethird of migraine patients suffer from migraine aura, a perceptual disturbance preceding the typically unilateral headache. Cortical spreading depression (CSD), a ... 
Machine learning framework for assessment of microbial factory performance
(Plos ONE, 20190101)Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess ... 
Lessons from Two Design–Build–Test–Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning
(ACS Synthetic Biology, 20190101)The Design–Build–Test–Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient ... 
Glioma invasion and its interplay with the nervous tissue: a multiscale model
(2019)A multiscale mathematical model for glioma cell migration and proliferation is proposed, taking into account a possible therapeutic approach. Starting with the description of processes taking place on the subcellular level, ... 
SDEdriven modeling of phenotypically heterogeneous tumors: The influence of cancer cell stemness
(Discrete and Continuous Dynamical Systems  Series B, 2019)We deduce cell population models describing the evolution of a tumor (possibly interacting with its environment of healthy cells) with the aid of differential equations. Thereby, different subpopulations of cancer cells ... 
Tissue drives lesion: computational evidence of interspecies variability in cardiac radiofrequency ablation
(HE 10TH INTERNATIONAL CONFERENCE ON FUNCTIONAL IMAGING AND MODELING OF THE HEART, 2019)Radiofrequency catheter ablation (RFCA) is widely used for the treatment of various types of cardiac arrhythmias. Typically, the efficacy and the safety of the ablation protocols used in the clinics are derived from tests ... 
How does radiofrequency ablation efficacy depend on the stiffness of the cardiac tissue? Insights from a computational model
(2019)Objective. Radiofrequency catheter ablation (RFCA) is an effective treatment for the elimination of cardiac arrhythmias, however it is not exempt from complications that can risk the patients’ life. The efficacy of the ... 
Qualitative analysis of kineticbased models for tumorimmune system interaction
(Discrete and Continuous Dynamical Systems  Series B, 201808)A mathematical model, based on a mesoscopic approach, describing the competition between tumor cells and immune system in terms of kinetic integrodifferential equations is presented. Four interacting populations are ... 
Computational predictive modeling of integrated cerebral metabolism, electrophysiology and hemodynamics
(20190212)Understanding the energetic requirement of brain cells during resting state and during high neuronal activity is a very active research area where mathematical models have contributed significantly by providing a context ... 
Anticipation via canards in excitable systems
(Chaos: An Interdisciplinary Journal of Nonlinear Science, 20190114)Neurons can anticipate incoming signals by exploiting a physiological mechanism that is not well understood. This article offers a novel explanation on how a receiver neuron can predict the sender’s dynamics in a ... 
Atomistic Insight into Ion Transport and Conductivity in Ga/AlSubstituted Li$_7$La$_3$Zr$_2$O$_{12}$ Solid Electrolytes
(ACS Applied Materials & Interfaces, 20180109)Garnetstructured Li$_{7}$La$_{3}$Zr$_{2}$O$_{12}$ is a promising solid electrolyte for nextgeneration solidstate Li batteries. However, sufficiently fast Liion mobility required for battery applications only emerges ... 
A leastsquares implicit RBFFD closest point method and applications to PDEs on moving surfaces
(Journal of Computational Physics, 201810)The closest point method (Ruuth and Merriman, J. Comput. Phys. 227(3):19431961, [2008]) is an embedding method developed to solve a variety of partial differential equations (PDEs) on smooth surfaces, using a closest point ... 
ProC congruence properties for groups of rooted tree automorphisms
(Archiv der Mathematik, 20181121)We propose a generalisation of the congruence subgroup problem for groups acting on rooted trees. Instead of only comparing the profinite completion to that given by level stabilizers, we also compare pro$\mathcal{C}$ ...