Seminars and Colloquia by Series

Distinguishing mechanisms of immunopathology in COVID-19 using virtual patient cohorts

Series
Mathematical Biology Seminar
Time
Wednesday, January 19, 2022 - 10:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Morgan CraigUniversity of Montréal

Please Note: Meeting Link: https://bluejeans.com/426529046/8775

Two years after the beginning of the pandemic, we are still working to understand the mechanisms of immunopathology in COVID-19. Immune responses following SARS-CoV-2 infections are heterogeneous, and biomarkers of this variability remain to be elucidated. In collaboration with experimentalists and clinicians, we have deployed various mathematical and computational approaches to understand longitudinal immunological data from patients, and to generate new hypotheses about the factors determining COVID-19 severity and disease dynamics.
To answer foundational questions about immunopathology and heterogeneity in COVID-19, we have developed a multi-scale, mechanistic mathematical model of the immune response to SARS-CoV-2 that includes several innate and adaptive immune cells and their communication via signalling networks. By generating a population of virtual patients, we identified dysregulated rates of monocyte-to-macrophage differentiation that distinguishes disease severity in these in silico patients. Further, our results suggest that maximal IL-6 concentrations can be used as a predictive biomarker of CD8+ T cell lymphopenia. Using the same cohort of virtual patients, we have also studied the influence of variant on immunopathology by combining our model with data of intra-host viral evolution. We predicted that the combined effects of mutations affecting the spike proteins and interferon evasion on the severity of COVID-19 are mostly determined by the innate host immune response. Our approaches can be used to study the factors regulated immunopathology during SARS-CoV-2 infections, and represent a quantitative framework for the study of COVID-19 and other viral diseases.

Data-driven mechanistic modeling for personalized oncology

Series
Mathematical Biology Seminar
Time
Wednesday, November 17, 2021 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Heiko EnderlingMoffitt Cancer Center

Please Note: Meeting Link: https://bluejeans.com/379561694/5031

In close collaboration with experimentalists and clinicians, mathematical models that are parameterized with experimental and clinical data can help estimate patient-specific disease dynamics and treatment success. This positions us at the forefront of the advent of ‘virtual trials’ that predict personalized optimized treatment protocols. I will discuss a couple of different projects to demonstrate how to integrate calculus into clinical decision making. I will present a variety of mathematical model that can be calibrated from early treatment response dynamics to forecast responses to subsequent treatment. This may help us to identify patient candidates for treatment escalation when needed, and treatment de-escalation without jeopardizing outcomes.

Recording link: https://bluejeans.com/s/dcDrDQuxm2W

The topology of nucleic acids

Series
Mathematical Biology Seminar
Time
Wednesday, November 10, 2021 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Mariel VazquezUniversity of California, Davis

Please Note: Meeting Link: https://bluejeans.com/379561694/5031

Multiple cellular processes such as replication, recombination, and packing change the topology of nucleic acids. The genetic code of viruses and of living organisms is encoded in very long DNA or RNA molecules, which are tightly packaged in confined environments. Understanding the geometry and topology of nucleic acids is key to understanding the mechanisms of viral infection and the inner workings of a cell. We use techniques from knot theory and low-dimensional topology, aided by discrete methods and computational tools, to ask questions about the topological state of a genome. I will illustrate the use of these methods with examples drawn from recent work in my group.

 

Recording link: https://bluejeans.com/s/bQ3pI0YI2f5

An agent-based model of the tumour microenvironment

Series
Mathematical Biology Seminar
Time
Wednesday, October 20, 2021 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Cicely MacnamaraUniversity of Glasgow

Please Note: Meeting Link: https://bluejeans.com/379561694/5031

The term cancer covers a multitude of bodily diseases, broadly categorized by having cells which do not behave normally. Cancer cells can arise from any type of cell in the body; cancers can grow in or around any tissue or organ making the disease highly complex. My research is focused on understanding the specific mechanisms that occur in the tumour microenvironment via mathematical and computational modelling. In this talk I shall present a 3D individual-based force-based model for tumour growth and development in which we simulate  the behavior of, and spatio-temporal interactions between, cells, extracellular matrix fibres and blood vessels. Each agent is fully realised, for example, cells are described as viscoelastic sphere with radius and centre given within the off-lattice model. Interactions are primarily governed by mechanical forces between elements. However, as well as the mechanical interactions we also consider chemical interactions, by coupling the code to a finite element solver to model the diffusion of oxygen from blood vessels to cells, as well as intercellular aspects such as cell phenotypes. 

Using simple baseline models to interpret developmental processes in C. elegans

Series
Mathematical Biology Seminar
Time
Wednesday, October 13, 2021 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Niall M. ManganNorthwestern University

Please Note: Meeting Link: https://bluejeans.com/379561694/5031

Growth control establishes organism size, requiring mechanisms to sense and adjust growth. Studies of single cells revealed that size homeostasis uses distinct control methods: Size, Timer, and Adder. In multicellular organisms, mechanisms that regulate single cell growth must integrate control across organs and tissues during development to generate adult size and shape. We leveraged the roundworm Caenorhabditis elegans as a scalable and tractable model to collect precise growth measurements of thousands of individuals, measure feeding behavior, and quantify changes in animal size and shape. Using quantitative measurements and mathematical modeling, we propose two models of physical mechanisms by which C. elegans can control growth. First, constraints on cuticle stretch generate mechanical signals through which animals sense body size and initiate larval-stage transitions. Second, mechanical control of food intake drives growth rate within larval stages. These results suggest how physical constraints control developmental timing and growth rate in C. elegans.

https://www.biorxiv.org/content/10.1101/2021.04.01.438121v2

Recording link: https://bluejeans.com/s/9NyLSfq4tGD

Inferring hybridization features from genomic sequences under the network multispecies coalescent model

Series
Mathematical Biology Seminar
Time
Wednesday, September 29, 2021 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Hector BanosDalhousie University

Please Note: Meeting Link: https://bluejeans.com/379561694/5031

Hybridization plays an important role during the evolutionary process of some species. In such cases, phylogenetic trees are sometimes insufficient to describe species-level relationships. We show that most topological features of a level-1 species network (a network with no interlocking cycles) are identifiable under the network multi-species coalescent model using the logDet distance between aligned DNA sequences of concatenated genes. 

 

 

Maximizing insight with minimal (and erroneous) information: The case of COVID-19

Series
Mathematical Biology Seminar
Time
Wednesday, September 15, 2021 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Juan B. GutiérrezUniversity of Texas at Saint Antonio

Please Note: Meeting Link: https://bluejeans.com/379561694/5031

This talk presents novel approaches to old techniques to forecast COVID-19: (i) a modeling framework that takes into consideration asymptomatic carriers and government interventions, (ii) a method to rectify daily case counts reported in public databases, and (iii) a method to study socioeconomic factors and propagation of disinformation. In the case of (i), results were obtained with a comprehensive data set of hospitalizations and cases in the metropolitan area of San Antonio through collaboration with local and regional government agencies, a level of data seldom studied in a disaggregated manner. In the case of (ii), results were obtained with a simple approach to data rectification that has not been exploited in the literature, resulting in a non-autonomous system that opens avenues of mathematical exploration. In the case of (iii), this talk presents a methodology to study the effect of socioeconomic and demographic factors, including the phenomenon of disinformation and its effect in public health; currently there are few mathematical results in this important area.

Global Constraints within the Developmental Program of the Drosophila Wing

Series
Mathematical Biology Seminar
Time
Friday, April 30, 2021 - 15:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Madhav ManiNorthwestern University

Organismal development is a complex process, involving a vast number of molecular constituents interacting on multiple spatio-temporal scales in the formation of intricate body structures. Despite this complexity, development is remarkably reproducible and displays tolerance to both genetic and environmental perturbations. This robustness implies the existence of hidden simplicities in developmental programs. Here, using the Drosophila wing as a model system, we develop a new quantitative strategy that enables a robust description of biologically salient phenotypic variation. Analyzing natural phenotypic variation across a highly outbred population, and variation generated by weak perturbations in genetic and environmental conditions, we observe a highly constrained set of wing phenotypes. Remarkably, the phenotypic variants can be described by a single integrated mode that corresponds to a non-intuitive combination of structural variations across the wing. This work demonstrates the presence of constraints that funnel environmental inputs and genetic variation into phenotypes stretched along a single axis in morphological space. Our results provide quantitative insights into the nature of robustness in complex forms while yet accommodating the potential for evolutionary variations. Methodologically, we introduce a general strategy for finding such invariances in other developmental contexts. -- https://www.biorxiv.org/content/10.1101/2020.10.13.333740v3

Meeting Link: https://gatech.bluejeans.com/348270750

Mutation probabilities and moments of step functions

Series
Mathematical Biology Seminar
Time
Friday, April 16, 2021 - 15:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Zvi RosenFlorida Atlantic University

Suppose that n sample genomes are collected from the same population. The expected sample frequency spectrum (SFS) is the vector of probabilities that a mutation chosen at random will appear in exactly k out of the n individuals. This vector is known to be highly dependent on the population size history (demography); for this reason, geneticists have used it for demographic inference. What does the set of all possible vectors generated by demographies look like? What if we specify that the demography has to be piecewise-constant with a fixed number of pieces? We will draw on tools from convex and algebraic geometry to answer these and related questions.

Meeting Link: https://gatech.bluejeans.com/348270750

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