Mathematical models are routinely calibrated to experimental data, with goals ranging from
building predictive models to quantifying parameters that cannot be measured. Whether or …

Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these
phenomena can influence a cell's fitness by conferring access to heritable, beneficial …

The stochasticity of gene expression presents significant challenges to the modeling of
genetic networks. A two-state model describing promoter switching, transcription, and …

Many experiments show that the numbers of mRNA and protein are proportional to the cell
volume in growing cells. However, models of stochastic gene expression often assume …

Although molecular mechanisms that prompt cell-cycle arrest in response to DNA damage
have been elucidated, the systems-level properties of DNA damage checkpoints are not …

Cell size varies during the cell cycle and in response to external stimuli. This requires the
tight coordination, or" scaling," of mRNA and protein quantities with the cell volume in order …

Epithelial-mesenchymal heterogeneity implies that cells within the same tumor can exhibit
different phenotypes—epithelial, mesenchymal, or one or more hybrid epithelial …

The cell cycle is canonically described as a series of four consecutive phases: G1, S, G2,
and M. In single cells, the duration of each phase varies, but the quantitative laws that …

Skeletal muscle fibers are multinucleated cells that contain mostly myofibrils suspended in
an aqueous media termed the sarcoplasm. Select evidence suggests sarcoplasmic …

Intracellular reaction rates depend on concentrations and hence their levels are often
regulated. However classical models of stochastic gene expression lack a cell size …