A semantics, energy-based approach to automate biomodel composition

Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.

Atmospheric characterization of hot Jupiters using hierarchical models of Spitzer observations

The field of exoplanet atmospheric characterization is trending towards comparative studies involving many planetary systems, and using Bayesian hierarchical modelling is a natural next step. Here we demonstrate two use cases. We first use hierarchical modelling to quantify variability in repeated observations by reanalyzing a suite of ten Spitzer secondary eclipse observations of the hot Jupiter XO-3b. We compare three models: one where we fit ten separate eclipse depths, one where we use a single eclipse depth for all ten observations, and a hierarchical model. By comparing the Widely Applicable Information Criterion of each model, we show that the hierarchical model is preferred over the others. The hierarchical model yields less scatter across the suite of eclipse depths—and higher precision on the individual eclipse depths—than does fitting the observations separately. We find that the hierarchical eclipse depth uncertainty is larger than the uncertainties on the individual eclipse depths, which suggests either slight astrophysical variability or that single eclipse observations underestimate the true eclipse depth uncertainty. Finally, we fit a suite of published dayside brightness measurements for 37 planets using a hierarchical model of brightness temperature versus irradiation temperature. The hierarchical model gives tighter constraints on the individual brightness temperatures than the non-hierarchical model. Although we tested hierarchical modelling on Spitzer eclipse data of hot Jupiters, it is applicable to observations of smaller planets like hot neptunes and super earths, as well as for photometric and spectroscopic transit or phase curve observations.

A method to reduce ELISA serial dilution assay workload applied to SARS-CoV-2 and seasonal HCoVs

Objectives Assays using ELISA measurements on serially diluted serum samples have been heavily used to measure serum reactivity to SARS-CoV-2 antigens and are widely used in virology and elsewhere in biology. We test a method to reduce the workload of these assays, and measure reactivity of SARS-CoV-2 and HCoV antigens to human serum samples collected before and during the COVID-19 pandemic. Methods We apply Bayesian hierarchical modelling to ELISA measurements of human serum samples against SARS-CoV-2 and HCoV antigens. Results Inflection titers for SARS-CoV-2 full-length spike protein (S1S2), spike protein receptor-binding domain (RBD), and nucleoprotein (N) inferred from three spread-out dilutions correlated with those inferred from eight consecutive dilutions with an R2 value of 0.97 or higher. We confirm existing findings showing a small proportion of pre-pandemic human serum samples contain cross-reactive antibodies to SARS-CoV-2 S1S2 and N, and that SARS-CoV-2 infection increases serum reactivity to the beta-HCoVs OC43 and HKU1 S1S2. Conclusions In serial dilution assays, large savings in resources and/or increases in throughput can be achieved by reducing the number of dilutions measured and using Bayesian hierarchical modelling to infer inflection or endpoint titers. We have released software for conducting these types of analysis.