CBBS Subgroup Contributed Talks

Thursday, June 17 at 06:45am (PDT)
Thursday, June 17 at 02:45pm (BST)
Thursday, June 17 10:45pm (KST)

SMB2021 SMB2021 Follow Wednesday (Thursday) during the "CT09" time block.
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Prasenjit Ghosh

PhD Candidate, Indian Institute of Science, Bengaluru, India
"Discrete particulate modeling of cell nuclei"
The nucleus of a cell plays a pivotal role in regulating cellular function and providing mechanical integrity. We present a three-dimensional discrete particle model of the nucleus that incorporates the nuclear lamina and chromatin-containing nucleoplasm. The exterior, including the lamina, is modeled by a shell of bonded particles that can exhibit elastic, geometrically nonlinear, and buckling characteristics. The interior, comprising the viscous fluid-like nucleoplasm and the elastic chromatin meshwork, is modeled with particles that undergo viscoelastic interactions. Such a particle framework allows for a realistic representation of the discreteness in nuclear structure and heterogeneity in nuclear properties. In addition, contact dynamics between particles is naturally handled within this framework. This is advantageous when considering the dynamic linkages between intranuclear components (chromatin and the lamina) or between the nucleus and the cytoskeleton. The efficacy of this particle model is compared with different experimental assays, and relevant insights are provided.

Benjamin Wölfl

University of Vienna, Vienna Graduate School of Population Genetics
" On branch length distributions in the coalescent and its application in the i-ton density score"
Efficient backward-time and forward-time simulation of simple to complex evolutionary scenarios are combined in order to describe the branch length distributions of branches with i underlying leaves in the extant sample in the correlated coalescent trees across linked loci in the genetic basis of a single independent trait. This takes into account the effect of genetic linkage on the decay of coalescent tree correlation across neighboring loci. Specifically, also the distributional shape under polygenic adaptation is investigated. Generally, there is no analytical expression for these branch length distributions which raises the importance of a computational insight. Ultimately, this distribution is used in order to construct a hypothesis test of selection versus no selection which does not only make use of singletons as in the singleton density score (SDS), but generally the density of i-tons via the newly introduced i-ton density score (IDS) test statistic. In this way, attention is placed on the characteristics of this distribution under different evolutionary scenarios, in particular when we are not only facing a simple recent hard selective sweep. Among other organisms, this method may then for instance be applied to human genetic data sets.

Diego Samuel Rodrigues

"A Bayesian Framework for Mathematical Modeling of In Vivo Pharmacokinetic Profiles of Magnetic Particles"
This contribution is about a Bayesian framework devoted to parameter estimation of an ordinary differential equation (ODE) model describing pharmacokinetic (PK) profiles of magnetic nanoparticles. Data comes from in vivo experiments in which one injected the nanoparticles into the bloodstream and measured them by alternate current biosusceptometry both in the heart and liver. The non-linear ODE model comprises three compartments, one for the heart and the other two for the liver, from which the nanoparticles partially return to the bloodstream. Reported simulations and calibration of curves and parameters were performed in R language using FME Package and others. As for results, it includes uncertainty analysis, credibility regions, and an identifiability discussion. As a perspective, we intend to use the described methodology for investigating possible changes in PK profiles originated by liver cancers. This work is supported by funding from grant #2020/05556-0, São Paulo Research Foundation (FAPESP).

Jackie Taylor

University of Minnesota, Twin Cities
" An advection-diffusion-aggregation model for the colony formation and vertical motility of Microcystis aeruginosa"
The cyanobacterium Microcystis aeruginosa is one of the most common algal species capable of forming harmful algal blooms. There are two key traits related to the ubiquity of M. aeruginosa: colony formation under stressful environmental conditions and vertical motility via buoyancy regulation. While the importance and mechanisms of these traits have been thoroughly investigated, there is currently no model of M. aeruginosa transport and population dynamics that couples colony formation and motility. This talk will introduce such a model, consisting of a system of partial differential equations describing (i) the vertical diffusion of M. aeruginosa colonies in a stratified lake environment, (ii) the vertical advection of M. aeruginosa colonies as a function of water temperature and colony size, and (iii) a Smoluchowski term for the aggregation of colonies due to Brownian motion, shear, and differential settling. Model results will be compared to field trends, and the promises and perils of the method will be discussed.

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Virtual conference of the Society for Mathematical Biology, 2021.