Significant technological advances made in recent years have shepherded a dramatic increase in utilization of digital technologies for biomedicine– everything from the widespread use of electronic health records to… 

May 10, 2022 • 4:00 – 5:30

Cardiology Conference Room, Laboratory for Systems Medicine

Online registries offer many advantages for research, including the ability to efficiently assess large numbers of individuals and identify potential participants for clinical trials and genetic studies.

Aspergillus species are ubiquitous environmental moulds, with spores inhaled daily by most humans.

Luis Sordo Vieira will present at 11:00 PT to the AMS Special Session on Mathematical Models for Biomolecular and Cellular Interactions at the Joint Mathematics Meetings.

On April 9 at 9:00 PT, Reinhard Laubenbacher will present a paper to the AMS Special Session on Current Advances in Computational Biomedicine at the Virtual 2022 Joint Mathematics Meetings.

On April 11 at 16:00, Reinhard Laubenbacher will present to the Texas A&M University Mathematics colloquium.

On April 12 at 18:00, Reinhard Laubenbacher will deliver the 2022 Sue Geller Undergraduate Lecture at Texas A&M University.

Connecting evolutionary genetics and ecological dynamics with multi-strain pathogen models

Comparison of ODE and Agent-Based Approaches to Pharmacokinetic Pharmacodynamic Models

Dory: Overcoming Barriers to Computing Persistent Homology

This project seeks to develop a novel approach to the modular design of multi-scale models using virtual machines and a user friendly open-source platform. Availability of biomedical data sets across spatial and temporal scales makes it possible to calibrate complex models that capture integrated processes from the molecular to the whole organism level.

The project addresses an important biomedical problem: how to control biofilms formed by Candida albicans, a dimorphic fungus that is an important cause of both topical and systemic fungal infection in humans, in particular immunocompromised patients.

Multiscale modeling of disease requires the integration of data at various spatiotemporal scales. Extending these models is often challenged by complex computational implementations and interdependencies between components of the model. In this project, we are developing a computational blueprint so that computational models can be developed in a modular fashion, while minimizing interdependencies between model components.

Network analysis has gained popularity in systems medicine, though most applications have been “out of the box”. Cutting-edge network science draws from the rich history of graph theory and recent developments in statistical modeling and is aided by the speed, storage, and interoperability of computational resources. These distinctive research projects showcase the broader potential of network methods.