Anne‐Kristin Kaster

This study examines microbial community dynamics in a photobioreactor using agricultural waste gas streams, showing spatially structured communities and partial nitrogen recovery.

This study shows engineered DNA materials influence microbial physiology and community dynamics by altering stress responses and shaping genetic interactions in wastewater microbiomes.

MOFTy disentangles spatial structures and recovers cross-modal patterns in multi-omics data by separating smooth gradients from fine-scale heterogeneity.

The paper introduces PE-TFD, a method using protein embeddings and machine learning to discover novel protein functions, demonstrating its effectiveness in identifying hydrogenases not found by traditional methods.

This study investigates the relationship between grapevine trunk diseases, the rhizomicrobiome, and soil chemistry, finding that microbial interactions, not just pathogen presence, drive disease outbreaks.

This study identifies chlorophyll a degradation in prokaryotes using structural homology and metagenomic data, revealing widespread metabolic capabilities across diverse taxa.

The paper investigates how drought affects bacterial communities in maize rhizosphere root channels and identifies functional adaptations in response to water stress.

This study uses machine learning and experimental validation to annotate hypothetical proteins in E. coli K-12, demonstrating the power of combining omics data with AI.

The paper introduces a new method called Midi-metagenomics for improving microbial genome reconstruction by using cell sorting to create targeted fractions, avoiding amplification biases and enhancing MAG quality.