Mathematics Dept.
  Events
MIT
Mon 13 Jul 2020, 9:00am
Probability Seminar
Online (see Angel, Murugan or Perkins for link)
Simplicity and Complexity in Belief Propagation I
Online (see Angel, Murugan or Perkins for link)
Mon 13 Jul 2020, 9:00am-10:00am

Abstract

 There is a very simple algorithm for the inference of posteriors for probability Markov models on trees. Asymptotic properties of this algorithm were first studied in statistical physics and have later played a role in coding theory, in machine learning, and in evolutionary inference, among other areas.  The lectures will highlight various phase transitions for this model and their connections to modern statistical inference. Finally we show that, perhaps unexpectedly, this ``simple algorithm" requires complex computation in a number of models. 
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MIT
Tue 14 Jul 2020, 9:00am
Probability Seminar
Online (see Angel, Murugan or Perkins for link)
Simplicity and Complexity in Belief Propagation II
Online (see Angel, Murugan or Perkins for link)
Tue 14 Jul 2020, 9:00am-10:00am

Abstract

There is a very simple algorithm for the inference of posteriors for probability Markov models on trees. Asymptotic properties of this algorithm were first studied in statistical physics and have later played a role in coding theory, in machine learning, and in evolutionary inference, among other areas.  The lectures will highlight various phase transitions for this model and their connections to modern statistical inference. Finally we show that, perhaps unexpectedly, this ``simple algorithm" requires complex computation in a number of models. 
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MIT
Wed 15 Jul 2020, 9:10am
Probability Seminar
Online (see Angel, Murugan or Perkins for link)
Simplicity and Complexity in Belief Propagation III
Online (see Angel, Murugan or Perkins for link)
Wed 15 Jul 2020, 9:10am-10:00am

Abstract

 There is a very simple algorithm for the inference of posteriors for probability Markov models on trees. Asymptotic properties of this algorithm were first studied in statistical physics and have later played a role in coding theory, in machine learning, and in evolutionary inference, among other areas.  The lectures will highlight various phase transitions for this model and their connections to modern statistical inference. Finally we show that, perhaps unexpectedly, this ``simple algorithm" requires complex computation in a number of models. 
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Vanderbilt University
Wed 15 Jul 2020, 1:45pm
Mathematical Biology Seminar
Zoom
Something's wrong in the (cellular) neighborhood: Mechanisms of epithelial wound detection
Zoom
Wed 15 Jul 2020, 1:45pm-2:45pm

Abstract

The first response of epithelial cells to local wounds is a dramatic increase in cytosolic calcium. This increase occurs quickly – calcium floods into damaged cells within 0.1 s, moves into adjacent cells over ~20 s, and appears in a much larger set of surrounding cells via a delayed second expansion over 40-300 s – but calcium is nonetheless a reporter: cells must detect wounds even earlier. Using the calcium response as a proxy for wound detection, we have identified an upstream G-protein-coupled-receptor (GPCR) signaling pathway, including the receptor and its chemokine ligand. We present experimental and computational evidence that multiple proteases released during cell lysis/wounding serve as the instructive signal, proteolytically liberating active ligand to diffuse to GPCRs on surrounding epithelial cells. Epithelial wounds are thus detected by the activation of a protease bait. We will discuss the experimental evidence and a corresponding computational model developed to test the plausibility of these hypothesized mechanisms. The model includes calcium currents between each cell’s cytosol and its endoplasmic reticulum (ER), between cytosol and extracellular space, and between the cytosol of neighboring cells. These calcium currents are initiated in the model by cavitation-induced microtears in the plasma membranes of cells near the wound (initial influx), by flow through gap junctions into adjacent cells (first expansion), and by the activation of GPCRs via a proteolytically activated diffusible ligand (second expansion). We will discuss how the model matches experimental observations and makes experimentally testable predictions.

Supported by NIH Grant 1R01GM130130.
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Alfréd Rényi Institute of Mathematics
Wed 29 Jul 2020, 10:00am
Topology and related seminars
Online (Ask Liam Watson or Ben Williams for the Zoom link)
TBA
Online (Ask Liam Watson or Ben Williams for the Zoom link)
Wed 29 Jul 2020, 10:00am-11:00am

Abstract

 TBA
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University of Melbourne
Wed 29 Jul 2020, 1:50pm
Mathematical Biology Seminar
Zoom - see PIMS remote seminars for details
Mathematical modelling of the emergence and spread of antimalarial drug resistance
Northwestern University
Fri 25 Sep 2020, 2:45pm
Mathematical Biology Seminar
ESB 4133
TBA
ESB 4133
Fri 25 Sep 2020, 2:45pm-3:45pm

Abstract

 TBA

Note for Attendees

 Prof Volkening will also deliver the Rising Stars colloquium on Nov 6, 2020.
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Adrianne Jenner
Universite de Montreal
Wed 14 Oct 2020, 1:45pm
Mathematical Biology Seminar
TBD
Improving oncolytic virotherapy using hybrid PDE/agent-based models and ODE systems
TBD
Wed 14 Oct 2020, 1:45pm-2:45pm

Abstract

Developing effective cancer treatment presents a unique challenge due to the overwhelming variability in tumour cell behaviour and spatial heterogeneity. Virotherapy is a type of cancer treatment that uses genetically engineered viruses to infect and lyse cancerous cells. When these viruses are administered with immune cells or immunostimulatory cytokines, an antitumour immune response is instigated. Developing a hybrid PDE/agent-based modelling for the treatment of glioblastoma (a type brain cancer), we predicted the variability in glioblastoma cells that hinders the efficacy of oncolytic virotherapy. We then show how this treatment could be improved for the majority of patients. Recently, gel-based mediums have been used to improve the efficacy of oncolytic virotherapy by providing a sustained therapeutic delivery of the vectors . Using a system of ODEs and a genetic algorithm, we show how this treatment could be further optimised by changing the gel-material to reduce the immune cell release rate. Overall, this talk aims to demonstrate complementing mathematical models and their applications in oncolytic virotherapy.
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Northwestern University
Fri 6 Nov 2020, 3:00pm SPECIAL
Department Colloquium
ESB 1012
TBA
ESB 1012
Fri 6 Nov 2020, 3:00pm-4:00pm

Abstract

 TBA

Note for Attendees

 Rising Stars Colloquium
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ETH Zurich, will move to NYU
Fri 20 Nov 2020, 3:00pm
Department Colloquium
TBD
Faculty of Science Early Career Invited Lecture: TBD
TBD
Fri 20 Nov 2020, 3:00pm-3:50pm

Abstract


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UC Irvine
Thu 18 Mar 2021, 3:30pm SPECIAL
Diff. Geom, Math. Phys., PDE Seminar
TBA
TBA
TBA
Thu 18 Mar 2021, 3:30pm-4:30pm

Abstract

 
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UC Irvine
Fri 19 Mar 2021, 3:00pm
Department Colloquium
TBA
PIMS-UBC Rising Star Colloquium
TBA
Fri 19 Mar 2021, 3:00pm-4:00pm

Abstract

 
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Conor Mooney
Fri 19 Mar 2021, 3:00pm SPECIAL
Rising Star Colloquium
Fri 19 Mar 2021, 3:00pm-4:00pm

Details

 
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Ciprian Manolescu
Stanford University
Fri 26 Mar 2021, 3:00pm
Department Colloquium
ESB1012
PIMS-UBC Distinguished Colloquium
ESB1012
Fri 26 Mar 2021, 3:00pm-4:00pm

Abstract

 
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