IMAG/MSM Working Group on Multiscale Modeling and Viral Pandemics Mini Seminars
April 21, 2022
Welcome - The meeting will start at 3PM ET
NOTE: THE MEETING WILL BE RECORDED, STREAMED AND PUBLICLY AVAILABLE�FOR THOSE UNABLE TO ATTEND
Agenda
People
Co-Lead: Reinhard Laubenbacher, PhD
Department of Medicine
Laboratory for Systems Medicine
University of Florida
reinhard.laubenbacher@medicine.ufl.edu
Co-Lead: James A. Glazier, PhD
Dept. of Intelligent Systems Engineering and Biocomplexity Institute
Indiana University, Bloomington
Web Administration, Slack: James P. Sluka, PhD
Dept. of Intelligent Systems Engineering and Biocomplexity Institute
Indiana University, Bloomington
Activities Coordination: Lorenzo Veschini, PhD
King’s College London
Slack Channel
https://Msm-working-group.slack.com
Our IMAG/MSM Wiki page
https://www.imagwiki.nibib.nih.gov/working-groups/multiscale-modeling-and-viral-pandemics Feel free to suggest additional content!
Or, use the Tiny URL: https://tinyurl.com/hkr97vfe
IMAG’s LinkedIn
YouTube “MSM Working Group on Multiscale Modeling” https://www.youtube.com/channel/UCuDFvhgFziRRDcpRnT3vlrw �see also the links on our seminar page at https://tinyurl.com/5fra7jjd
Please follow the�group on Twitter!
If you could re-tweet the weekly announcements �(there are usually two, one for each speaker) �that would help boost attendance and community awareness.
Announcements
�
Any short (~1 minute) items such as;
Schedule for Upcoming Meetings and mini-Seminars
April 28:
May 5:
May 12:
May 19:
Request for future speakers (May 5, …)
Mini-Seminar�Multi-scale modelling reveals that early super-spreader events are a likely contributor to novel variant predominance
Daniel Reeves�Fred Hutchinson Cancer Research Center.
SARS-CoV-2 variants of concern have been characterized to varying degrees by higher transmissibility, worse infection outcomes and evasion of vaccine and infection-induced immunologic memory. Here we present a multi-scale model of SARS-CoV-2 dynamics that describes population spread through individuals whose viral loads and numbers of contacts (drawn from an over-dispersed distribution) are both time-varying. This stochastic framework allows us to explore how super-spreader events contribute to variant emergence.
Mini-Seminar�Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using EGRIN and PRIME
Nitin Baliga�Institute for System Biology
The ability of Mycobacterium tuberculosis (Mtb) to adopt heterogeneous physiological states underlies its success in evading the immune system and tolerating antibiotic killing. Drug tolerant phenotypes are a major reason why the tuberculosis (TB) mortality rate is so high, with over 1.8 million deaths annually. To develop new TB therapeutics that better treat the infection (faster and more completely), a systems-level approach is needed to reveal the complexity of network-based adaptations of Mtb. I will present two predictive models called EGRIN and PRIME to uncover environment-specific vulnerabilities within the regulatory and metabolic networks of Mtb. (Time permitting) I will also show how the models were used to uncover how combinatorial gene regulation enables C. difficile growth relative to commensal colonization in the mouse gut.
Requests for Input/Suggestions
We would like the subgroup leads to prepare brief presentations for the Thursday meetings, please let us know when you would like to present
Ideas/help for publicising our Thursday mini-seminars more effectively and for speakers to invite
Suggestions for agenda items and approaches to organizing the Steering Committee Meetings more effectively
There have also been a number of requests for more explicit statements of goals and tasks from the WG leadership, we would appreciate your suggestions
Please contact Reinhard Laubenbacher, James Glazier, James Sluka or Lorenzo Veschini with your ideas on all of these issues
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