Anders Miki Bojesen

The paper integrates holo-omic data from porcine hosts and gut microbiomes to predict host-microbiome interactions, identifying both known and novel relationships.

The paper develops three diagnostic tests for Aspergillus fumigatus infection in chickens using methylation markers from serum cell-free DNA and machine learning, achieving high accuracy.

This study uses deep learning-based tracking to detect behavioral changes in infected poultry, showing reduced activity in E. coli-infected chickens compared to controls.

This paper introduces MSSM, a method for high-resolution spatial metagenomics that enables strain-level analysis of gut microbiomes at the microscale.