Veronika B. Dubinkina

Linkage of nucleotide and functional diversity varies across gut bacteria.

The paper examines genomic diversity in gut bacteria, finding that accessory genes show faster linkage decay compared to core SNPs, with mobile genetic elements showing minimal linkage to core SNPs.

Self-supervised learning enables robust microbiome predictions in data-limited and cross-cohort settings

This paper develops self-supervised learning models for gut microbiome metagenomic data, showing improved prediction performance in data-limited and cross-cohort settings.

Accurate estimation of intraspecific microbial gene content variation in metagenomic data with MIDAS v3 and StrainPGC

The paper introduces StrainPGC and MIDAS v3 to accurately estimate intraspecific microbial gene content variation in metagenomic data, outperforming existing methods and revealing functional diversity in gut microbiomes.

FUN-PROSE: A Deep Learning Approach to Predict Condition-Specific Gene Expression in Fungi

FUN-PROSE predicts condition-specific gene expression in fungi using promoter sequences and transcription factor data, achieving high correlation with observed expression.