Peter F. Arndt

This study improves the estimation of evolutionary distances and tree inference by accounting for substitution rate heterogeneity across prokaryotic genomes.

The paper models horizontal gene transfer as a stochastic process over a bacterial genus network and uses match length distributions to infer transfer patterns and network topology.

commonPeak identifies common ChIP-seq peaks across conditions and protocols using equivalence testing, finding 225 shared estrogen receptor peaks with similar enrichment in breast cancer cells.

The paper identifies genomic features and signatures associated with increased segmental duplication rates through network analysis of duplication events.

The paper derives an analytical formula for the distribution of distances between heterozygous sites in diploid species to infer demographic history without simplifying assumptions.

The paper identifies over 100,000 horizontal gene transfer events across 90,000 bacterial genomes, revealing frequent long-distance genetic exchange and its functional impact.

The paper predicts cancer cell-of-origin from DNA sequences by matching mutational landscapes to chromatin modification patterns in normal tissues.

The paper analyzes de novo mutations in humans to show large-scale mutation rate variation and its relationship with divergence and diversity, finding biased gene conversion weakens divergence-mutation correlations.