Donate Weghorn

The paper identifies a hypermutation hotspot at transcription start sites in the human germline, linked to early embryogenesis and distinct from known mutagenic processes.

This study links EPAS1HIF2 genetic adaptations in high-altitude populations to similar mutations in hypoxia-driven tumors, showing shared mechanisms in hypoxia response and tumorigenesis.

This study profiles mutations in MMR-deficient human cells and identifies new mutational signatures linked to MMR deficiency and cancer development.

This paper extends the Walsh-Hadamard transform to model epistasis in genetic landscapes with multiple alleles per position, enabling analysis of pairwise and higher-order interactions in simulated and empirical data.

The paper introduces SigNet, a deep learning method for mutational signature decomposition, showing improved accuracy and robustness in estimating signature contributions in cancer genomes.

This study identifies novel cancer driver genes by analyzing mutation nucleotide contexts in whole-exome sequencing data from 12,004 tumors.

The paper assesses the applicability of the mutation-selection balance model to human protein-truncating variants using simulations and data from exome datasets.

The paper estimates genome-wide selection coefficients for heterozygous protein truncating variants using exome data from 60,706 individuals and identifies genes under strong selection.