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Understanding the evolutionary dynamics created by a given evolutionary algorithm is a critical step in determining which ones are most likely to produce desirable outcomes for a given problem. While it is relatively easy to come up with hypotheses that could plausibly explain observed evolutionary outcomes, we often fail to take the next step of confirming that our proposed mechanism accurately describes the underlying evolutionary dynamics. Visualization is a powerful tool for exploring evolutionary history as it actually played out. We can create visualizations that summarize the evolutionary history of a population or group of populations by drawing representative lineages on top of the fitness landscape being traversed. This approach integrates information about the adaptations that took place with information about the evolutionary pressures they were being subjected to as they evolved. However, these visualizations can be challenging to depict on a two-dimensional surface, as they integrate multiple forms of three-dimensional (or more) data. Here, we propose an alternative: taking advantage of recent advances in virtual reality to view evolutionary history in three dimensions. This technique produces an intuitive and detailed illustration of evolutionary processes. A demo of our visualization is available here: https://emilydolson.github.io/fitness_landscape_visualizations.
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The effects of evolutionary adaptations on spreading processes in complex networks
A common theme among previously proposed models for network epidemics is the assumption that the propagating object (e.g., a pathogen [in the context of infectious disease propagation] or a piece of information [in the context of information propagation]) is transferred across network nodes without going through any modification or evolutionary adaptations. However, in real-life spreading processes, pathogens often evolve in response to changing environments and medical interventions, and information is often modified by individuals before being forwarded. In this article, we investigate the effects of evolutionary adaptations on spreading processes in complex networks with the aim of 1) revealing the role of evolutionary adaptations on the threshold, probability, and final size of epidemics and 2) exploring the interplay between the structural properties of the network and the evolutionary adaptations of the spreading process.
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- Award ID(s):
- 1813637
- PAR ID:
- 10137483
- Publisher / Repository:
- Proceedings of the National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 117
- Issue:
- 11
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- p. 5664-5670
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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