All possible repetitive crystal structures!
219 of them.
20 minutes in optimal conditions, with a crazy multiple start sites mechanism: E. Coli starts DNA replication before the previous one finished.
Otherwise, naively, would take 60-90 minutes just to replicate and segregate the full DNA otherwise. So it starts copying multiple times.
- biology.stackexchange.com/questions/30080/how-can-e-coli-proliferate-so-rapidly
- stochasticscientist.blogspot.co.uk/2012/02/how-e-coli-grows-so-fast.html
- www.ncbi.nlm.nih.gov/pmc/articles/PMC2063475/ Organization of sister origins and replisomes during multifork DNA replication in Escherichia coli by Fossum et al (2007)
E. Coli Whole Cell Model by Covert Lab Install and first run by 
Ciro Santilli 37 Updated 2025-07-16
Ciro Santilli 37 Updated 2025-07-16At 7e4cc9e57de76752df0f4e32eca95fb653ea64e4 you basically need to use the Docker image on Ubuntu 21.04 due to pip breaking changes... (not their fault). Perhaps pyenv would solve things, but who has the patience for that?!?!
The Docker setup from README does just work. The image download is a bit tedius, as it requires you to create a GitHub API key as described in the README, but there must be reasons for that.
Once the image is downloaded, you really want to run is from the root of the source tree:This mounts the host source under The meaning of each of the analysis commands is described at Section "Output overview".
sudo docker run --name=wcm -it -v "$(pwd):/wcEcoli" docker.pkg.github.com/covertlab/wholecellecolirelease/wcm-full/wcEcoli, so you can easily edit and view output images from your host. Once inside Docker we can compile, run the simulation, and analyze results with:make clean compile &&
python runscripts/manual/runFitter.py &&
python runscripts/manual/runSim.py &&
python runscripts/manual/analysisVariant.py &&
python runscripts/manual/analysisCohort.py &&
python runscripts/manual/analysisMultigen.py &&
python runscripts/manual/analysisSingle.pyAs a Docker refresher, after you stop the container, e.g. by restarting your computer or running
sudo docker stop wcm, you can get back into it with:sudo docker start wcm
sudo docker run -it wcm bashrunscripts/manual/runFitter.py takes about 15 minutes, and it generates files such as reconstruction/ecoli/dataclasses/process/two_component_system.py (related) which is required to run the simulation, it is basically a part of the build.runSim.py does the main simulation, progress output contains lines of type:Time (s) Dry mass Dry mass Protein RNA Small mol Expected
(fg) fold change fold change fold change fold change fold change
======== ======== =========== =========== =========== =========== ===========
0.00 403.09 1.000 1.000 1.000 1.000 1.000
0.20 403.18 1.000 1.000 1.000 1.000 1.000 2569.18 783.09 1.943 1.910 2.005 1.950 1.963
Simulation finished:
- Length: 0:42:49
- Runtime: 0:09:13It would be boring if we could only simulate the same condition all the time, so let's have a look at the different boundary conditions that we can apply to the cell!
We are able to alter things like the composition of the external medium, and the genome of the bacteria, which will make the bacteria behave differently.
The variant selection is a bit cumbersome as we have to use indexes instead of names, but one you know what you are doing, it is fine.
Of course, genetic modification is limited only to experimentally known protein interactions due to the intractability of computational protein folding and computational chemistry in general, solving those would bsai.
Besides time series run variants, conditions can also be selected directly without a time series as in:which select row indices from so
python runscripts/manual/runSim.py --variant condition 1 1reconstruction/ecoli/flat/condition/condition_defs.tsv. The above 1 1 would mean the second line of that file which starts with:"condition" "nutrients" "genotype perturbations" "doubling time (units.min)" "active TFs"
"basal" "minimal" {} 44.0 []
"no_oxygen" "minimal_minus_oxygen" {} 100.0 []
"with_aa" "minimal_plus_amino_acids" {} 25.0 ["CPLX-125", "MONOMER0-162", "CPLX0-7671", "CPLX0-228", "MONOMER0-155"]1 means no_oxygen.where:
Remember that is a 4-vetor, gamma matrices are 4x4 matrices, so the whole thing comes down to a dot product of two 4-vectors, with a modified by matrix multiplication/derivatives, and the result is a scalar, as expected for a Lagrangian.
Like any other Lagrangian, you can then recover the Dirac equation, which is the corresponding equations of motion, by applying the Euler-Lagrange equation to the Lagrangian.
Some usage examples under: Section "Sequelize example".
As of 2021, this library is extremely painful to use. It does feel semi-mature, but there are just too much horrible things going on;
- the documentation is a bit messy and misses a lot of stuff. The examples are often too short, and it is hard to understand what specific options they are talking about do because they lack clear input/expected output pairs. Examples:
- the implementation has several inelegant/unintuitive annoyances/requirements of code repetition that drive you mad.The association API feels notably bad, it took a few days for Ciro Santilli to learn to do what he considers "basic" association operations, knowledge which he dumped to: stackoverflow.com/questions/22958683/how-to-implement-many-to-many-association-in-sequelize/67973948#67973948See also: how to decide if an ORM is good?.
- bugs are piling up. It appears that many key devs left, and current maintainers are just not being able to keep up.
Some glaring issues are listed at the horrors of Sequelize.
Formal name: "animalia".
TODO compare with actual datasetes.
The very first chapter opens with Grand Commander Hou disrespecting spirits by opening up a sealed tomb and unintentionally releasing 108 demons who presumably reincarnate as humans, a backstory to the events that follow years later.
This is well shown in the Japanese The Water Margin, but is skipped in the Chinese The Water Margin unfortunately.
Actually, now that Ciro Santilli thinks about it, these were already likely meant as a "collectible" element by the author of the original book, as is strongly suggested by all the little illustrations of each character present on the Wikipedia page. Just like e.g. Catholic saints. It's Pokemon, but 2000 years earlier.
Ciro would notably feel many years later, that as he met random people online who were interested in improving eduction, or was otherwise networking to reach his goals, as if he were actually building up his 108 stars of destiny.
A central part, and perhaps the most interesting part of the novel, is how each character has been motivated by injustice to join the rebellion. This reminds Ciro of Final Fantasy VI
Unfortunately, due to lack of one page to rule them all, the on-Git tree publication list is meager, some of the most relevant ones seems to be:
- 2021 open access review paper: journals.asm.org/doi/full/10.1128/ecosalplus.ESP-0001-2020 "The E. coli Whole-Cell Modeling Project". They should just past that stuff in a README :-) The article mentions that it is a follow up to the previous M. genitalium whole cell model by Covert lab. Only 43% of known genes modelled at this point however, a shame.
- 2020 under Science paywall: www.science.org/doi/10.1126/science.aav3751 "Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation"
By Tagkopoulos lab at University of California, Davies.
- www.nature.com/articles/ncomms13090 Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli (2016)
- www.sciencedaily.com/releases/2016/10/161027173552.htm
Reference strain: E. Coli K-12 MG1655.
Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.
Figure 3. Visual Studio Code extension installation.
Figure 5. . You can also edit articles on the Web editor without installing anything locally. Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension. 
- Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact