Anna R. Panchenko

This study uses molecular dynamics and cryo-ET to show histone tails drive chromatin compaction through specific interactions, revealing their role in both structural organization and nucleosome communication.

This study examines how the G34R and G33R mutations in histone H3.3 affect nucleosome structure and dynamics using NMR and molecular dynamics simulations.

The paper assesses the oncogenic potential of histone missense mutations using whole-exome sequencing data from over 12,000 cancer patients, finding that these mutations affect DNA repair interactions and increase mutagenesis.

The paper evaluates domain-based methods for identifying cancer driver mutations by aggregating mutations across protein domains and mutation types, finding improved classification performance with domain similarity.

This study evaluates next-generation pathogenicity predictors for cancer driver mutation detection, finding they perform well but lack specificity for cancer types.

The paper introduces NuPose, a deep residual network for predicting nucleosome positions and associated features across the genome with high accuracy.

The paper develops a computational method to predict cell-type-specific nucleosome-binding abilities of transcription factors using ChIP-seq, MNase-seq, and DNase-seq data, identifying new potential pioneer transcription factors.

The paper shows survivin interacts with PRC2, preventing H3K27 methylation and gene silencing in CD4+T cells.