Nikolaos Vakirlis

The paper investigates the evolutionary origins of protein novelty in Saccharomycotina yeasts, identifying two distinct modes of de novo and divergent gene evolution and their structural implications.

The paper distinguishes expressed orphan genes from spurious ones and conserved genes in the human gut microbiome using metatranscriptomic data and machine learning.

The paper uses machine learning to identify diverged orphan genes from similarity search outputs, finding that ~30% of simulated orphans are predicted to be divergent.

The paper analyzes the pan-transcriptome of yeast isolates to show that accessory genes significantly contribute to gene expression variation across populations.

The paper analyzes degradation determinants in canonical and noncanonical human proteins, finding noncanonical proteins are enriched for degradation features and that C-terminal hydrophobicity correlates with degradation propensity.

The paper investigates TM-forming potential in intergenic regions of Saccharomycotina yeasts and finds it is pervasive but variable across species.

The paper investigates positional preferences of gene duplicates in S. cerevisiae, finding SSD and WGD genes occupy distinct chromosomal niches with different structural and regulatory features.