Alex Gavryushkin

This study compares machine learning methods for predicting phenotypes from genetic data, finding that transformers outperform others in simulations and match state-of-the-art models on real data.

This paper introduces a Bayesian method for summarizing phylogenetic tree posteriors using clade probabilities, showing it performs as well or better than existing methods.

The paper proves that time-dependent fossilised birth-death models are identifiable, but shows that adding a removal after sampling parameter makes them unidentifiable.

The paper introduces an automated convergence diagnostic for phylogenetic MCMC analyses, demonstrating high accuracy in detecting convergence issues and enabling real-time evaluation.

This paper introduces a method to estimate the mean in the space of ranked phylogenetic trees, demonstrating its effectiveness across real datasets.

The paper introduces a fast Lasso-based method, Pint, for inferring three-way gene interactions in large-scale genetic data, outperforming existing methods in simulated and real datasets.

This paper introduces SNVformer, a Transformer-based model for GWAS data that predicts gout from SNVs with 83% AUROC, showing promise for scalable genotype-phenotype association analysis.

The paper introduces an online Bayesian phylogenetic inference algorithm for BEAST 2 that allows efficient updates to analyses as data changes, without re-running from scratch.

This paper evaluates factors predicting bioinformatic software accuracy and finds that sustained development, not citations or journal impact, is most indicative of accuracy.

The paper develops a model to infer pairwise epistatic gene interactions from siRNA perturbation screens, showing that glinternet outperforms xyz in accuracy for high-dimensional data.

The paper introduces a fast Lasso-based method for detecting epistatic interactions in large-scale genotype-phenotype screens, demonstrating its application on simulated and real data.

This paper analyzes the geometry of the ranked nearest neighbour interchange graph for phylogenetic trees, finding exact radius and diameter values and comparing it to the classical NNI graph.

This study investigates how bacterial interactions in the Drosophila gut microbiome influence host fitness traits like development, reproduction, and lifespan.