Assessment of Simulated Surveillance Testing and Quarantine in a SARS-CoV-2-Vaccinated Population of Students on a University Campus.

Importance: The importance of surveillance testing and quarantine on university campuses to limit SARS-CoV-2 transmission needs to be reevaluated in the context of a complex and rapidly changing environment that includes vaccines, variants, and waning immunity. Also, recent US Centers for Disease Control and Prevention guidelines suggest that vaccinated students do not need to participate in surveillance testing.

Objective: To evaluate the use of surveillance testing and quarantine in a fully vaccinated student population for whom vaccine effectiveness may be affected by the type of vaccination, presence of variants, and loss of vaccine-induced or natural immunity over time.

The Local Edge Machine: inference of dynamic models of gene regulation.

We present a novel approach, the Local Edge Machine, for the inference of regulatory interactions directly from time-series gene expression data. We demonstrate its performance, robustness, and scalability on in silico datasets with varying behaviors, sizes, and degrees of complexity. Moreover, we demonstrate its ability to incorporate biological prior information and make informative predictions on a well-characterized in vivo system using data from budding yeast that have been synchronized in the cell cycle.