Alexander T. Bahcheli

This study reassesses human mitochondrial DNA methylation using multiple platforms and finds signals likely due to technical artifacts rather than biological methylation.

The paper develops a deep learning model to predict mutation density in metastatic cancers using chromatin accessibility data from primary tumors, showing lineage-linked chromatin context influences regional mutagenesis.

The paper examines therapy-associated mutagenesis at CTCF binding sites across 4,870 tumor genomes, finding increased mutation enrichment at these sites under radiotherapy and trifluridine treatment.

The paper identifies mutational signatures in cancer genomes that alter protein sequence motifs in signaling networks, linking mutation etiology to functional consequences.

The paper identifies immunogenomic interactions across 13 cancer types using a multi-omics framework, linking genomic alterations and immune features to patient survival.

The paper introduces DPM, a directional integration method for multi-omics data that identifies consistent gene and pathway changes across datasets and highlights inconsistent evidence.

This paper presents a telomere-to-telomere genome assembly of Phaeodactylum tricornutum using Oxford Nanopore long reads, identifying 25 nuclear chromosomes and improving genetic engineering opportunities.

The paper identifies genetic variants affecting phosphorylation sites in human proteins involved in SARS-CoV-2 infection and COVID-19, showing rewiring of signaling networks.

The paper presents a strategy to complete and validate metagenome-assembled genomes using a combination of short and ultra-long reads, resulting in multiple complete genomes from a bacterial community.