Published Articles

Our lab’s publications, from current and past members.

California Exodus? A Network Model of Population Redistribution in the United States

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The California Exodus, where droves of population are leaving California and settling in other U.S. states, has recently received broad media coverage, but less attention in scientific research. In a recent paper published in Journal of Mathematical Sociology, NCASD researchers Peng Huang and Carter Butts analyze the population redistribution pattern in the United States. They […]

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Parameter estimation procedures for exponential-family random graph models on count-valued networks: A comparative simulation study

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The exponential-family random graph models (ERGMs) have emerged as an important framework for modeling a wide variety of relational types. ERGMs for valued networks are less well-developed than their unvalued counterparts, and pose particular computational challenges. Network data with edge values on the non-negative integers (count-valued networks) is an important such case, with examples ranging

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Probing Protein Adaptations in Extreme Environments

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Extremophiles are organisms that thrive, or at least tolerate, extreme environmental conditions, such as the high temps and pressures found near under-water hydrothermal vents, or the freezing temperatures of permafrost soils. To survive these uncomfortable climates, organisms have had to undergo adaptations, specifically molecular adaptations that change the behavior between their biomacromolecules to reflect the

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Network Analysis Uncovers Advantageous Adaptations in a Viral Enzyme

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A year’s worth of mutations to the SARS-CoV-2 main protease (Mpro) were analyzed by NCASD member Elizabeth M. Diessner, in collaboration with Gemma R. Takahashi from the Martin Lab, to investigate how adaptations of the viral protein may contribute to the spread of the virus behind the Covid-19 pandemic. Published in Biochemistry, this paper details

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Network Hamiltonian Models Provide Access to Scalable Protein Aggregation Simulations

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Aggregation of γD-crystallin proteins in the eye lens are a known cause of both genetic and age-related cataract disease. Models of these aggregates are difficult to produce due to the size and complexity of traditional Molecular Dynamics (MD) simulations. In this paper, published in The Journal of Physical Chemistry B, NCASD member Liz Diessner and

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graph depicting probability of infection based on intermediate vertex count

Use of Social Contact Networks to Study COVID-19 Diffusion Drivers in Cities

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With the explosive increase in COVID-19 infections across urban environments during March of 2020, questions about how it spreads unevenly across cities needed to be addressed. NCASD researchers Loring Thomas, Peng Huang, Fan Yin, Junlan Xu and Carter Butts, in collaboration with John Hipp and NCASD alumnus Zack Almquist (University of Washington) investigated the geographical

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Novel Use Of Neural Nets To Convert PSNs To 3D Atomistic Structures

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  A recent collaboration between Dr. Vy Duong, Dr. Gianmarc Grazioli, and current NCASD member Liz Diessner, published in Biomolecules, illustrates the utility of Neural Networks for retrieving atomistic detail from Protein Structure Networks (PSNs) to reconstruct 3D molecular models. The ability to convert between coarse-grained PSNs and their detailed atomistic structure analogs allows researchers

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Reactive oxygen bang, illustrated in a hand-drawn comic style.

Studying Radical Movements Under Pressure

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Radiation is a hazard to all living organisms, damaging cellular systems at the molecular level.  Much of this damage is not due to the direct impact of radiation on cells, but the interaction of radiation with water to produce reactive oxygen species that react with and degrade biomolecules.  Like tiny bombs, these small molecules diffuse through the

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Social Network Analytic techniques used to probe changes in structure and dynamics of the SARS-CoV-2 Main Protease

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The main protease (Mpro) of SARS-CoV-2, the virus behind the global Covid-19 pandemic, is an essential part of the virus’ reproduction cycle once it has infected human cells. After viral RNA is transcribed into a long poly-protein, Mpro frees itself and other viral proteins from the poly-protein. NCASD researchers Liz Diessner and Carter Butts, in

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