| Start Date: | 1/28/2022 | Start Time: | 1:00 PM |
| End Date: | 1/28/2022 | End Time: | 3:00 PM |
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Event Description
BIOMED PhD Thesis Defense
Title:
Understanding How Time and Memory Interact with Network Topology in Real-World Systems with Selected Applications
Speaker:
Adam George Craig, PhD Candidate
School of Biomedical Engineering, Science and Health Systems
Drexel University
Advisors:
Andres Kriete, PhD
Associate Dean for Academic Affairs
Teaching Professor
School of Biomedical Engineering, Science and Health Systems
Drexel University
Uri Hershberg, PhD
Associate Professor
Department of Human Biology
University of Haifa
School of Biomedical Engineering, Science and Health Systems
Drexel University
Abstract:
Networks are an increasingly common way of summarizing complex systems, especially those in which interacting components transmit information. We here show that reintroducing motion and memory to these static representations of nodes and edges provides new insights into network structure. In particular, we show that spectral dimension, a random-walk based measure of network dimensionality, relates more strongly to the kinds of community structure found in a wide variety of real-world biological networks than do shortest-path based methods of calculating network fractal dimension and that MBRW generalized spectral dimension is a more effective means of exploring the heterogeneity of such networks than is simple random walk (RW) spectral dimension. Additionally, we find that all the measures considered show a pronounced finite size effect over the range of sizes within which the real-world networks fall (fewer than 10,000 nodes), reflecting the disparity between the infinite recursive hierarchy of structure implied by the concept of fractality and the limited sizes of networks describing real-world systems.
However, the systematic study of complex systems, including the scientific community itself, demands not only analytical methods but infrastructure for managing the descriptions of their components and interactions. To this end, we propose an approach to using the Nexus-PORTAL-DOORS (NPDS) metadata and data management system to store semantic representations of the statements and attributions of those statements found in scholarly research articles in order to better trace the flow of ideas from paper to paper and compare it to the network of citations in order to measure adherence to good citation practices and promote proper attribution in a way that will eventually be able to scale with the ever-growing output of the modern biomedical science and engineering community. |
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Audience:
Undergraduate StudentsGraduate StudentsFacultyStaff |
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