Vera B. Kaiser

This study shows that genetic background and environmental factors determine the trajectory of cancer evolution in mice, with distinct mutational paths despite similar final tumor states.

This study uses machine learning on ATAC-seq and RNA-seq data to predict CTCF-anchored chromatin loops during human meiosis, revealing dynamic changes in loop structure and function across meiotic stages.

The paper investigates how strand-asymmetric processes like replication and transcription influence DNA damage, repair, and mutagenesis, revealing mechanisms that shape cancer genome evolution.

The paper identifies mutational biases at germline regulatory sites, showing increased structural variants and insertions at transcription factor binding sites, with implications for evolution and disease.

The paper identifies chromatin loop anchors (LAPs) as sites of genomic instability in cancer and recombination hotspots in the germline, showing enrichment for structural variants and meiotic recombination.

The paper identifies response eQTLs that modify genetic regulation during immune activation and shows their enrichment in autoimmune disease GWAS signals.