Roeland C. H. J. van Ham

The paper evaluates how incomplete PPI networks contribute to functional annotation across species, showing improved performance with additional data sources like text mining.

The paper shows that unsupervised protein sequence embeddings outperform traditional features in predicting molecular function, with a simple model achieving state-of-the-art results.

The paper introduces MLC, a method that improves gene function prediction by weighting RNA-Seq samples based on Gene Ontology terms, outperforming standard Pearson correlation.