Emerging whole-cell modeling principles and methods

TL;DR

This paper reviews emerging principles and methods for whole-cell modeling, highlighting recent technological advances and ongoing efforts to develop scalable, comprehensive models of cellular behavior with potential applications in bioscience and medicine.

Contribution

It synthesizes recent progress in measurement, bioinformatics, and modeling techniques to guide the development of scalable, accurate whole-cell models.

Findings

Recent technological advances enable more comprehensive models

Progress in rule-based and multi-algorithmic simulation methods

Ongoing efforts aim to model human cells accurately

Abstract

Whole-cell computational models aim to predict cellular phenotypes from genotype by representing the entire genome, the structure and concentration of each molecular species, each molecular interaction, and the extracellular environment. Whole-cell models have great potential to transform bioscience, bioengineering, and medicine. However, numerous challenges remain to achieve whole-cell models. Nevertheless, researchers are beginning to leverage recent progress in measurement technology, bioinformatics, data sharing, rule-based modeling, and multi-algorithmic simulation to build the first whole-cell models. We anticipate that ongoing efforts to develop scalable whole-cell modeling tools will enable dramatically more comprehensive and more accurate models, including models of human cells.