We introduce a stochastic branching process model of diversity in recurrent tumors whose
growth is driven by drug resistance. Here, an initially declining population can escape …

It is generally accepted that the initiation and progression of cancers is the result of somatic
clonal evolution. Despite many peculiarities, evolution within populations of somatic cells …

The distribution of fitness effects (DFE) of new mutations is a key parameter of molecular
evolution. The DFE can in principle be estimated by comparing the site frequency spectra …

The rate of adaptive evolution depends on the rate at which beneficial mutations are
introduced into a population and the fitness effects of those mutations. The rate of beneficial …

Estimation of the distribution of selection coefficients of mutations is a long-standing issue in
molecular evolution. In addition to population-based methods, the distribution can be …

Mutations are the ultimate source of variation used for evolutionary adaptation, while also
being predominantly deleterious and a source of genetic disorders. Understanding the rate …

The temporal dynamics of cancer evolution remain elusive, because it is impractical to
longitudinally observe cancers unperturbed by treatment. Consequently, our knowledge of …

The rate of mutations varies> 100-fold across the genome, altering the rate of evolution, and
susceptibility to genetic diseases. The strongest predictor of mutation rate is the sequence …

Stochastic models of sequential mutation acquisition are widely used to quantify cancer and
bacterial evolution. Across manifold scenarios, recurrent research questions are: how many …

Variation from new mutations is important for several questions in quantitative genetics. Key
parameters are the genomic mutation rate and the distribution of effects of mutations (DEM) …