Wholecell

Whole-cell modeling is an approach in computational biology that aims to simulate an entire living cell by integrating detailed representations of its molecular processes into a single, coherent model. A whole-cell model typically includes modules for metabolism, gene expression (transcription and translation), replication, cell division, regulation, and signaling, with the goal of producing realistic dynamics and phenotypes from genotype.

Historically, the concept gained traction with advances in systems biology and high-performance computing in the 2000s. A landmark early achievement was the whole-cell model of the bacterium Mycoplasma genitalium developed by Karr and colleagues, published in 2012, which combined multiple submodels to simulate cell growth, division, and gene expression. The work demonstrated feasibility and highlighted data gaps as well as the need for standardized modeling practices.

Methodologically, whole-cell models are usually constructed in a modular fashion, integrating dozens of submodels into a common simulation framework. They often employ a mix of stochastic and deterministic methods to represent gene expression, regulation, and signaling alongside continuous representations of metabolism. Subsecond to minute time scales may be simulated, depending on the organism and resolution. Building and running such models requires substantial computing resources and careful attention to data quality. Standards such as SBML (Systems Biology Markup Language) and related tools facilitate sharing and reuse of submodels, supporting reproducibility and community collaboration.

Impact and outlook: Whole-cell modeling provides a framework for hypothesis testing, experimental planning, and exploring genotype–phenotype relationships. It remains challenging to scale to more complex organisms due to data gaps, parameter uncertainty, and computational cost. Ongoing work seeks to expand coverage to additional organisms, improve data integration, and apply whole-cell models in synthetic biology and medicine.