M.A. Kazanskii

The paper identifies gene-specific evolutionary-rate associations with quantitative mammalian brain phenotypes using integrated phenotypic and genomic data.

This study evaluates machine learning's ability to predict ancient DNA age from damage profiles, finding no significant predictive power beyond baselines.

AutoRNA uses a variational autoencoder to predict RNA tertiary structures from sequences, achieving reasonable accuracy but limited global fold recovery.