One of the long-term goals of synthetic biology is to develop synthetic cells with unique capabilities for a wide range of medical and industrial applications, such as synthesizing complex drugs, detecting disease in deep tissues, and breaking down waste in remote regions. Like other engineering fields, these efforts would likely be accelerated by predictive models that help engineers rationally design synthetic biological systems. This requires more comprehensive and predictive models of biology. Due to the multiple scales involved in biological systems, these models must be able to capture how biological behavior emerges from the molecular level across multiple scales. Because no single experimental technology can completely characterize biology, these models must integrate multiple types of data.

Despite extensive knowledge and data, we still do not have a comprehensive, predictive understanding of biology. As a result, engineering biology remains a challenging, error-prone, and expensive process.

Several barriers remain to have the capabilities to construct, simulate, and apply comprehensive models of biology. Two key barriers are the lack of a language for describing such models and the lack of tools for simulating such models. Furthermore, we lack some of the basic ingredients necessary to build such tools.

The goal of this project was to accelerate the development of more comprehensive and more predictive models of cells by developing the computational methods and technologies needed to model and simulate how cellular behavior emerges from the molecular level.

We implemented these goals by developing WC-Lang, a language for systematically describing whole-cell models and WC-Sim, and a tool for executing models described in this language. Both tools introduce several innovations, not only for modeling cells, but for large-scale modeling more generally. This includes novel methods for modeling and simulating multiple scales, novel tools for tracking the provenance of models, and a new interface that we believe is better suited to viewing and editing large models.

We anticipate the WC-Lang and WC-Sim will accelerate the development of whole-cell models. Furthermore, by systemizing whole-cell modeling, we believe that WC-Lang and WC-Sim make it easier for researchers to contribute to whole-cell modeling, which will further accelerate its development. Ultimately, we believe that whole-cell models will help scientists gain insights into biology, help engineers design biology, and help physicians design precise therapies for individual patients.

To implement WC-Lang and WC-Sim, we developed several additional tools. DE-Sim makes it easier for researchers to build and execute complex simulations, BpForms and BcForms enable researchers to concretely describe physiological molecules, and ObjTables can help researchers publish higher-quality, more reusable datasets. Conv-opt makes it easier for modelers to solve optimization problems by providing a consistent interface to several optimization libraries.

We anticipate the BpForms and BcForms will accelerate the integration of knowledge of processes beyond the Central Dogma, such as epigenetic, post-transcriptional, and post-translational modification. Similarly, ObjTables has the potential to make it easier for scientists to share and reuse data, making it easier for scientists to integrate disparate facts into cohesive theories.

Last Modified: 02/09/2021
Modified by: Jonathan R Karr