Because sometimes you just want to simulate single prokaryotic biological living whole cell models starting from DNA to minute detail to understand how it works and predict simple experimental observations.
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Awesome whole cell simulation

1. The idea

I was thinking maybe something along:

  • precalculated interactivity of the molecules (simulated?!) to speed things up

  • then discretize cell spatially. TODO necessary? if yes, maybe a 2D slice type of model, on GPU? Model molecule concentration with time in each slot.

  • Then modify genome,, determine what proteins come out. Protein folding simulations?!

  • precalculate interactions of new proteins, and loop


  • can you get enough data out of a single cell? How long until it doubles? Do the cells interact with one another, and or change the extracelullar medium noticeably? Having single cells would be simpler and more precise.

    Another option is to make on huge cell in a Cell free environment:

2. Cell free

Since cells are themselves to complicated, maybe we can start with simplified DNA systems?

Maybe we can make insulin more efficiently by selecting only the parts of the cell we care about!


  • Compartmentalization of an all-E. coli Cell-Free Expression System for the Construction of a Minimal Cell. 2016. Filippo Caschera, Vincent Noireaux

  • Engine out of the chassis: Cell-free protein synthesis and its uses. 2013. Gabriel Rosenblum, Barry S. Cooperman.

  • Rapid and Scalable Preparation of Bacterial Lysates for Cell-Free Gene Expression. 2017. Andriy Didovyk, Taishi Tonooka, Lev Tsimring, and Jeff Hasty.

  • Developing cell-free biology for industrial applications. 2006. Jim Swartz.

  • Portable, On-Demand Biomolecular Manufacturing. 2016. Keith Pardee, Shimyn Slomovic, Peter Q. Nguyen, Christopher N. Boddy, Neel S. Joshi, James J. Collins.

3. Projects with source code

Shut up and give me the fine source.

4. Videos

Shut up and show me a visualisation.

5. Research areas

5.2. Gene editing

Ah, it would be even more awesome if we could hack up the cells and see them do stuff.

Heart only in second half 2010’s did it become possible to edit genes, but coding the entire DNA from scratch is still too expensive.

Previously, you would have to:

and then kill ones that didn’t get the gene, which is less reliable.

6. Papers

I guess this is what researchers do instead of blog posts. Go figure!

  • The principles of whole-cell modeling. Jonathan R Karr, Koichi Takahashi and Akira Funahashi

  • The Future of Whole-Cell Modeling. Derek N. Macklin, Nicholas A. Ruggero, and Markus W. Covert

  • Paper-Based Synthetic Gene Networks. Keith Pardee, Alexander A. Green, Tom Ferrante D. Ewen Cameron, Ajay DaleyKeyser, Peng Yin, and James J. Collins Wyss

  • Paper as a novel material platform for devices. Jason P. Rolland and Devin A. Mourey

  • A Whole-Cell Computational Model Predicts Phenotype from Genotype. Jonathan R. Karr, Jayodita C. Sanghvi, Derek N. Macklin, Miriam V. Gutschow, Markus Covert. Notes: Mycoplasma genitalium. Model apparently at:

8. What cell to use

8.1. Mycoplasma , e.g. Mycoplasma mycoides.

8.1.1. Mycoplasma genitalium

Size: 300 x 600 nm


  • 475 genes

  • 580 kbp

Downsides mentioned at

  • too small to see on light microscope

  • difficult to genetically manipulate. TODO why?

  • less literature than E. Coli.


8.2. E. Coli

Size: 1–2 micrometers long and about 0.25 micrometer in diameter, so: 2 * 0.5 * 0.5 * 10e-18 and thus 0.5 micrometer square.

Division time: 20 minutes, with a crazy multiple start sites mechanism:


  • 4k genes

  • 5 Mbps

8.4. C. Elegans

OK, not seriously considering multicellular beings, but maybe we can learn some experimental techniques:

8.5. Human

OK, lol.


  • 3 Gbps

  • 20k genes

11. Big projects, institutes and companies

12. Experimental


Manipulate individual cells:


DNA sequencing:

12.1. Mass spectroscopy

Potentially measure the quantities of every substance in the cell?

13. Cell behaviour

Random list of interesting cell behaviour that we have to model and might verify, in particular what kind of external environment they expect to encounter:

18. Data sources

Questions that beg for a database answer:

19. Low entry barrier

DIY off topic you don’t need to be a PhD type of resources for people like me

20. Molecular dynamics