Barbara A. Han

This study identifies Aminopeptidase N as the receptor for hedgehog merbecoviruses and shows restricted cross-species receptor use.

This paper predicts filovirus host susceptibility in bats by integrating molecular binding data with ecological and phylogenetic information across 1,300 species.

The paper uses explainable AI to predict food shortages in Eastern Australian flying foxes, identifying environmental and bat-level features that predict nutritional stress with high accuracy.

The paper uses machine learning to screen museum tissues for novel coronaviruses and paramyxoviruses, recovering sequences from archived samples and identifying new host species.

The paper develops a multi-scale statistical model to predict Hendra virus shedding in black flying foxes by integrating environmental and host condition factors across spatial and temporal scales.

The paper develops a knowledge graph to analyze highly pathogenic avian influenza, identifying new relationships and validating the utility of knowledge graphs in ecological systems.

The paper investigates how the pace of life in vertebrate hosts affects their potential to transmit mosquito-borne parasites, finding that fast-lived hosts generally have higher transmission potential.

The paper develops a data-driven model to predict potential Zika virus vectors by analyzing vector-virus trait combinations, identifying 35 species, including seven in the continental US.