M. Clara De Paolis Kaluza

This paper reports on the fourth CAFA challenge, showing improvements in Gene Ontology term prediction but highlighting challenges in new evaluation settings.

This work analyzes CAFA5 submissions, showing improved accuracy in protein function prediction and highlights the role of protein language models and 3D structures in performance gains.

The paper develops embeRNA, a method to predict microbial functions from 16S rRNA sequences without reference databases, showing better performance in novel environments.

This paper introduces a novel method to explore bacterial functional repertoires without reference databases, showing it outperforms existing approaches in taxonomic assignment and captures environment-driven diversity.