Project description:We develop an R/Bioconductor package CancerInSilico to simulate bulk and single cell transcriptional data from a known ground truth obtained from mathematical models of cellular systems. This package contains a general R infrastructure for cell-based mathematical model, implemented for an off-lattice, cell-center Monte Carlo mathematical model. We also adapt this model to simulate the impact of growth suppression by targeted therapeutics in cancer and benchmark simulations against bulk in vitro experimental data. Sensitivity to parameters is evaluated and used to predict the relative impact of variation in cellular growth parameters and cell types on tumor heterogeneity in therapeutic response.
Project description:The aim of the experiment was to obtain a time series data set of barcoded glioblastoma cells to use as input for a mathematical model of glioblastoma state transition and growth, to reconstruct the structure of the transition network, the transition rates, and individual growth rates of each state.
Project description:The aim of the experiment was to obtain a time series data set of barcoded glioblastoma cells to use as input for a mathematical model of glioblastoma state transition and growth, to reconstruct the structure of the transition network, the transition rates and individual growth rates of each state.
Project description:Proteome and transcriptome often show poor correlation, hindering the system-wide analysis of post-transcriptional regulation. Here, the authors study proteome and transcriptome dynamics during Drosophila embryogenesis and present basic mathematical models describing the temporal regulation of most protein-RNA pairs.
Project description:Proteome and transcriptome often show poor correlation, hindering the system-wide analysis of post-transcriptional regulation. Here, the authors study proteome and transcriptome dynamics during Drosophila embryogenesis and present basic mathematical models describing the temporal regulation of most protein-RNA pairs.
Project description:Proteomics and transcriptomics data of tomato fruits at 9 developmental stages were used to calculate with a mathematical model the rate constants of synthesis and degradation for over 1,000 proteins.