### TBD by Blair Sullivan

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, October 23, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Blair Sullivan – School of Computing, University of Utah

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- Series
- Mathematical Biology Seminar
- Time
- Wednesday, October 23, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Blair Sullivan – School of Computing, University of Utah

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, October 2, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Afaf Saaidi – Georgia Tech

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, September 25, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Daniel Cruz – Georgia Tech

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, September 18, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Hector Banos – Georgia Tech

When hybridization plays a role in evolution, networks are necessary to describe species-level relationships. In this talk, we show that most topological features of a level-1 species network (networks with no interlocking cycles) are identifiable from gene tree topologies under the network multispecies coalescent model (NMSC). We also present the theory behind NANUQ, a new practical method for the inference of level-1 networks under the NMSC.

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, September 11, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Bo Lin – Georgia Tech

Phylogenetic trees are the fundamental mathematical representation of evolutionary processes in biology. As data objects, they are characterized by the challenges associated with "big data," as well as the complication that their discrete geometric structure results in a non-Euclidean phylogenetic tree space, which poses computational and statistical limitations.

In this talk, I will compare the geometric and statistical properties between a well-studied framework - the BHV space, and an alternative framework that we propose, which is based on tropical geometry. Our framework exhibits analytic, geometric, and topological properties that are desirable for theoretical studies in probability and statistics, as well as increased computational efficiency. I also demonstrate our approach on an example of seasonal influenza data.

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, September 4, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Christine Heitsch – Georgia Tech

Understanding the folding of RNA sequences into three-dimensional structures is one of the fundamental challenges in molecular biology. For example, the branching of an RNA secondary structure is an important molecular characteristic yet difficult to predict correctly. However, recent results in geometric combinatorics (both theoretical and computational) yield new insights into the distribution of optimal branching configurations, and suggest new directions for improving prediction accuracy.

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, August 28, 2019 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Lyonia Bunimovich – Georgia Tech

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, August 21, 2019 - 11:00 for 30 minutes
- Location
- Skiles 006
- Speaker
- Christine Heitsch – Georgia Tech

A brief meeting to discuss the plan for the semester, followed by an informal discussion over lunch (most likely at Ferst Place).

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, March 27, 2019 - 10:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 005
- Speaker
- Dan Coombs – UBC (visiting Emory) – coombs@math.ubc.ca

The likelihood of HIV infection following risky contact is believed to be low. This suggests that the infection process is stochastic and governed by rare events. I will present mathematical branching process models of early infection and show how we have used them to gain insights into the duration of the undetectable phase of HIV infection, the likelihood of success of pre- and post-exposure prophylaxis, and the effects of prior infection with HSV-2. Although I will describe quite a bit of theory, I will try to keep giant and incomprehensible formulae to a minimum.

- Series
- Mathematical Biology Seminar
- Time
- Wednesday, February 27, 2019 - 11:01 for 1 hour (actually 50 minutes)
- Location
- Skiles 005
- Speaker
- Pavel Skums – GSU/CDC – skums@gsu.edu

Inference of evolutionary dynamics of heterogeneous cancer and viral populations Abstract: Genetic diversity of cancer cell populations and intra-host viral populations is one of the major factors influencing disease progression and treatment outcome. However, evolutionary dynamics of such populations remain poorly understood. Quantification of selection is a key step to understanding evolutionary mechanisms driving cancer and viral diseases. We will introduce a mathematical model and an algorithmic framework for inference of fitness landscapes of heterogeneous populations from genomic data. It is based on a maximal likelihood approach, whose objective is to estimate a vector of clone/strain fitnesses which better fits the observed tumor phylogeny, observed population structure and the dynamical system describing evolution of the population as a branching process. We will discuss our approach to solve the problem by transforming the original continuous maximum likelihood problem into a discrete optimization problem, which could be considered as a variant of scheduling problem with precedent constraints and with non-linear cumulative cost function.

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