Marina Abakarova

Proteome-wide prediction of the Functional Impact of Missense Variants with ProteoCast

ProteoCast predicts the functional impact of missense variants using evolutionary information, achieving high accuracy across the Drosophila proteome.

ProteoCast: a web server to predict, validate, and interpret missense variant effects

ProteoCast predicts and interprets missense variant effects using evolutionary and structural analysis, achieving high accuracy in pathogenicity prediction and identifying functional motifs in disordered regions.

Expert-guided protein Language Models enable accurate and blazingly fast fitness prediction

VespaG is a fast missense variant effect predictor using protein Language Models, achieving high accuracy on the ProteinGym benchmark.

Alignment-based protein mutational landscape prediction: doing more with less

The paper predicts mutational outcomes for 1.5M missense variants across 72 protein families using alignment-based methods, showing high-quality and compute-efficient results for entire proteomes.