Mathematics

Statistical Network Models for Integrating Functional Connectivity with sMRI and PET Brain Imaging Data

Speaker: 
James D. Wilson
Date: 
Wed, Nov 24, 2021
Location: 
Online
Abstract: 

Network analysis is one of the prominent multivariate techniques used to study structural and functional connectivity of the brain. In a network model of the brain, vertices are used to represent voxels or regions of the brain, and edges between two nodes represent a physical or functional relationship between the two incident regions. Network investigations of connectivity have produced many important advances in our understanding of brain structure and function, including in domains of aging, learning and memory, cognitive control, emotion, and disease. Despite their use, network methodologies still face several important challenges. In this talk, I will focus on a particularly important challenge in the analysis of structural and functional connectivity: how does one jointly model the generative mechanisms of structural and functional connectivity with other modalities? I propose and describe a statistical network model, called the generalized exponential random graph model (GERGM), that flexibly characterizes the network topology of structural and functional connectivity and can readily integrate other modalities of data. The GERGM also directly enables the statistical testing of individual differences through the comparison of their fitted models. In applying the GERGM to the connectivity of healthy individuals from the Human Connectome Project, we find that the GERGM reveals remarkably consistent organizational properties guiding subnetwork architecture in the typically developing brain. We will discuss ongoing work of how to adapt these models to neuroimaging cohorts associated with the ADRC at the University of Pittsburgh, where the goal is to relate the dynamics of structural and functional connectivity with tau and amyloid – beta deposition in individuals across the Alzheimer’s continuum.

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Single-molecule insights for DNA/RNA/protein interactions and drug discovery and development: the next level of resolution, for the next era of genetic medicines

Speaker: 
Sabrina Leslie
Date: 
Wed, Nov 3, 2021
Location: 
PIMS, University of British Columbia
Zoom
Online
Conference: 
Mathematical Biology Seminar
Abstract: 

Molecular interactions lie at the core of biochemistry and biology, and their understanding is crucial to the advancement of biotechnology, therapeutics, and diagnostics. Most existing tools make “ensemble” measurements and report a single result, typically averaged over millions of molecules or more. These measurements can miss rare events, averaging out the natural variations or sub-populations within biological samples, and consequently obscure insights into multi-step and multi-state reactions. The ability to make and connect robust and quantitative measurements on multiple scales - single molecules, cellular complexes, cells, tissues - is a critical unmet need. In this talk, I will introduce a general method called “CLiC” imaging to image molecular interactions one molecule at time with precision and control, and under cell-like conditions. CLiC works by mechanically confining molecules to the field of view in an optical microscope, isolating them in nanofabricated features, and eliminates the complexity and potential biases inherent to tethering molecules. By imaging the trajectories of many single molecules simultaneously and in a dynamic manner, CLiC allows us to investigate and discover the design rules and mechanisms which govern how therapeutic molecules or molecular probes interact with target sites on nucleic acids; and how molecular cargo is released inside cells from lipid nanoparticles. In this talk, I will discuss applications of our imaging platform to better understand DNA, RNA, protein interactions, as well as emerging classes of genetic medicines, gene editing and drug delivery systems. I will highlight current and potential future applications to connect our observations from the level of single molecule to single cells, and opportunities for collaboration as we set up our labs at UBC.

Class: 

The Tumor Growth Paradox

Speaker: 
Thomas Hillen
Date: 
Wed, Nov 10, 2021
Location: 
PIMS, University of Alberta
Zoom
Conference: 
Mathematical Biology Seminar
Abstract: 

The tumor invasion paradox relates to the artifact that a cancer that is exposed to increased cell death (for example through radiation), might spread and grow faster than before. The presence of cancer stem cells can convincingly explain this effect. In my talk I will use non-local and local reaction-diffusion type models to look at tumor growth and invasion speeds. We can show that in certain situations the invasion speed increases with increasing death rate - an invasion paradox (joint work with A. Shyntar and M. Rhodes).

Class: 

Skeleta for Monomial Quiver Relations

Speaker: 
Jesse Huang
Date: 
Wed, Dec 1, 2021
Location: 
PIMS, University of Alberta
Zoom
Online
Conference: 
Emergent Research: The PIMS Postdoctoral Fellow Seminar
Abstract: 

I will introduce a skeleton obtained directly from monomial relations in a finite quiver without cycles, and relate the construction to some classical examples in mirror symmetry. This is work in progress with David Favero.

Class: 

Solving clustering problems via new swarm intelligent algorithms

Speaker: 
Vardan Narula
Date: 
Wed, Nov 17, 2021
Location: 
Online
Abstract: 

In this work, improved swarm intelligent algorithms, namely, Salp Swarm Optimization algorithm, whale optimization, and Grasshopper Optimization Algorithm are proposed for data clustering. Our proposed algorithms utilize the crossover operator to obtain an improvised version of the existing algorithms. The performance of our suggested algorithms is tested by comparing the proposed algorithms with standard swarm intelligent algorithms and other existing algorithms in the literature. Non-parametric statistical test, the Friedman test, is applied to show the superiority of our proposed algorithms over other existing algorithms in the literature. The performance of our algorithms outperforms the performance of other algorithms for the data clustering problem in terms of computational time and accuracy.

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An Overview of Knots and Gauge Theory

Speaker: 
Edward Witten
Date: 
Tue, Nov 16, 2021
Location: 
PIMS, University of Saskachewan
quanTA
Zoom
Online
Conference: 
Peter Scherk Lecture in Geometry
Abstract: 

The Jones polynomial of a knot, discovered in 1983, is a very
subtle invariant that is related to a great deal of mathematics and
physics. This talk will be an overview of quantum field theories in
dimensions 2, 3, 4 and 5 that are intimately related to the Jones
polynomial of a knot and a more contemporary refinement of it that is known
as Khovanov homology.

Class: 

Differential Equations and Algebraic Geometry - 5

Speaker: 
Andreas Malmendier
Date: 
Mon, Nov 15, 2021
Location: 
PIMS, University of Alberta
Zoom
Online
Conference: 
PIMS Network Courses
Differential Equations and Algebraic Geometry
Abstract: 

This is a guest lecture in the PIMS Network Wide Graduate Course in Differential Equations in Algebraic Geometry.

Class: 

Differential Equations and Algebraic Geometry - 4

Speaker: 
Matt Kerr
Date: 
Fri, Nov 5, 2021
Location: 
PIMS, University of Alberta
Zoom
Online
Conference: 
PIMS Network Courses
Differential Equations and Algebraic Geometry
Abstract: 

This is a guest lecture in the PIMS Network Wide Graduate Course in Differential Equations in Algebraic Geometry.

Class: 

Differential Equations and Algebraic Geometry - 3

Speaker: 
Adrian Clingher
Date: 
Wed, Nov 3, 2021
Location: 
PIMS, University of Alberta
Zoom
Online
Conference: 
PIMS Network Courses
Differential Equations and Algebraic Geometry
Abstract: 

This is a guest lecture in the PIMS Network Wide Graduate Course in Differential Equations in Algebraic Geometry.

Class: 

Z_2 harmonic spinors in gauge theory

Speaker: 
Rafe Mazzeo
Date: 
Thu, Nov 18, 2021
Location: 
Zoom
Online
Conference: 
PIMS Network Wide Colloquium
Abstract: 

Gauge-theoretic moduli spaces are often noncompact, and various techniques have been introduced to study their asymptotic features. Seminal work by Taubes shows that in many situations where the failure of compactness for sequences of solutions is due to the noncompactness of the gauge group, diverging sequences of solutions lead to what he called Z_2 harmonic spinors. These are multivalued solutions of a twisted Dirac equation which are branched along a codimension two subset. This leads to a number of new problems related to these Z_2 harmonic spinors as interesting geometric objects in their own right. I will survey this subject and talk about some recent work in progress with Haydys and Takahashi to compute the index of the associated deformation problem.

Speaker Biography

Rafe Mazzeo is an expert in PDEs and Microlocal analysis. He did his PhD at MIT, and was then appointed as Szegő Assistant Professor at Stanford University, where he is now Professor and Chair of the Department of Mathematics. He has served the mathematical community in many important ways, including as Director of the Park City Mathematics Institute.

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