From this we see that there is a convention of naming promoters as protein name + p, e.g. the first gene in E. Coli K-12 MG1655 promoter thrLp encodes protein
thrL.It is also possible to add numbers after the TODO why 6 and 7? There don't appear to be 1, 2, etc.
p, e.g. at biocyc.org/ECOLI/NEW-IMAGE?type=OPERON&object=PM0-45989 we see that the protein zur has two promoters:zurp6zurp7
To modify the nutrients as a function of time, with To select a time series we can use something like:As mentioned in
python runscripts/manual/runSim.py --variant nutrientTimeSeries 25 25python runscripts/manual/runSim.py --help, nutrientTimeSeries is one of the choices from github.com/CovertLab/WholeCellEcoliRelease/blob/7e4cc9e57de76752df0f4e32eca95fb653ea64e4/models/ecoli/sim/variants/__init__.py#L5725 25 means to start from index 25 and also end at 25, so running just one simulation. 25 27 would run 25 then 26 and then 27 for example.The timeseries with index 25 is so we understand that it starts with extra amino acids in the medium, which benefit the cell, and half way through those are removed at time 1200s = 20 minutes. We would therefore expect the cell to start expressing amino acid production genes exactly at that point.
reconstruction/ecoli/flat/condition/timeseries/000025_cut_aa.tsv and contains"time (units.s)" "nutrients"
0 "minimal_plus_amino_acids"
1200 "minimal"nutrients likely means condition in that file however, see bug report with 1 1 failing: github.com/CovertLab/WholeCellEcoliRelease/issues/24When we do this the simulation ends in:so we see that the doubling time was faster than the one with minimal conditions of
Simulation finished:
- Length: 0:34:23
- Runtime: 0:08:030:42:49, which makes sense, since during the first 20 minutes the cell had extra amino acid nutrients at its disposal.The output directory now contains simulation output data under
out/manual/nutrientTimeSeries_000025/. Let's run analysis and plots for that:python runscripts/manual/analysisVariant.py &&
python runscripts/manual/analysisCohort.py --variant 25 &&
python runscripts/manual/analysisMultigen.py --variant 25 &&
python runscripts/manual/analysisSingle.py --variant 25We can now compare the outputs of this run to the default
wildtype_000000 run from Section "Install and first run".out/manual/plotOut/svg_plots/massFractionSummary.svg: because we now have two variants in the sameout/folder,wildtype_000000andnutrientTimeSeries_000025, we now see a side by side comparision of both on the same graph!The run variant where we started with amino acids initially grows faster as expected, because the cell didn't have to make it's own amino acids, so growth is a bit more efficient.Then, at 20 minutes, which is about 0.3 hours, we see that the cell starts growing a bit less fast as the slope of the curve decreases a bit, because we removed that free amino acid supply.
Figure 1. Minimal condition vs amino acid cut mass fraction plot. Source. From fileout/manual/plotOut/svg_plots/massFractionSummary.svg.
The following plots from under
out/manual/wildtype_000000/000000/{generation_000000,nutrientTimeSeries_000025}/000000/plotOut/svg_plots have been manually joined side-by-side with:for f in out/manual/wildtype_000000/000000/generation_000000/000000/plotOut/svg_plots/*; do
echo $f
svg_stack.py \
--direction h \
out/manual/wildtype_000000/000000/generation_000000/000000/plotOut/svg_plots/$(basename $f) \
out/manual/nutrientTimeSeries_000025/000000/generation_000000/000000/plotOut/svg_plots/$(basename $f) \
> tmp/$(basename $f)
done
Amino acid counts
. Source. aaCounts.svg:- default: quantities just increase
- amino acid cut: there is an abrupt fall at 20 minutes when we cut off external supply, presumably because it takes some time for the cell to start producing its own
External exchange fluxes of amino acids
. Source. aaExchangeFluxes.svg:- default: no exchanges
- amino acid cut: for all graphs except phenylalanine (PHE), either the cell was intaking the AA (negative flux), and that intake goes to 0 when the supply is cut, or the flux is always 0.For PHE however, the flux is at all times, except shortly after the cut. Why? And why there was no excretion on the default conditions?
mRNA count of highly expressed mRNAs
. Source. From file 
expression_rna_03_high.svg. Each of the entries is a gene using the conventional gene naming convention of xyzW, e.g. here's the BioCyc for the first entry, tufA: biocyc.org/gene?orgid=ECOLI&id=EG11036, which comments Elongation factor Tu (EF-Tu) is the most abundant protein in E. coli.
In E. coli, EF-Tu is encoded by two genes, tufA and tufB
External exchange fluxes
. Source. 
mediaExcange.svg: this one is similar to aaExchangeFluxes.svg, but it also tracks other substances. The color version makes it easier to squeeze more substances in a given space, but you lose the shape of curves a bit. The title seems reversed: red must be excretion, since that's where glucose (GLC) is.The substances are different between the default and amino acid cut graphs, they seem to be the most exchanged substances. On the amino cut graph, first we see the cell intaking most (except phenylalanine, which is excreted for some reason). When we cut amino acids, the uptake of course stops.
reconstruction/ecoli/flat/condition/nutrient/minimal.tsvcontains the nutrients in a minimal environment in which the cell survives:If we compare that to"molecule id" "lower bound (units.mmol / units.g / units.h)" "upper bound (units.mmol / units.g / units.h)" "ADP[c]" 3.15 3.15 "PI[c]" 3.15 3.15 "PROTON[c]" 3.15 3.15 "GLC[p]" NaN 20 "OXYGEN-MOLECULE[p]" NaN NaN "AMMONIUM[c]" NaN NaN "PI[p]" NaN NaN "K+[p]" NaN NaN "SULFATE[p]" NaN NaN "FE+2[p]" NaN NaN "CA+2[p]" NaN NaN "CL-[p]" NaN NaN "CO+2[p]" NaN NaN "MG+2[p]" NaN NaN "MN+2[p]" NaN NaN "NI+2[p]" NaN NaN "ZN+2[p]" NaN NaN "WATER[p]" NaN NaN "CARBON-DIOXIDE[p]" NaN NaN "CPD0-1958[p]" NaN NaN "L-SELENOCYSTEINE[c]" NaN NaN "GLC-D-LACTONE[c]" NaN NaN "CYTOSINE[c]" NaN NaNreconstruction/ecoli/flat/condition/nutrient/minimal_plus_amino_acids.tsv, we see that it adds the 20 amino acids on top of the minimal condition:so we guess that"L-ALPHA-ALANINE[p]" NaN NaN "ARG[p]" NaN NaN "ASN[p]" NaN NaN "L-ASPARTATE[p]" NaN NaN "CYS[p]" NaN NaN "GLT[p]" NaN NaN "GLN[p]" NaN NaN "GLY[p]" NaN NaN "HIS[p]" NaN NaN "ILE[p]" NaN NaN "LEU[p]" NaN NaN "LYS[p]" NaN NaN "MET[p]" NaN NaN "PHE[p]" NaN NaN "PRO[p]" NaN NaN "SER[p]" NaN NaN "THR[p]" NaN NaN "TRP[p]" NaN NaN "TYR[p]" NaN NaN "L-SELENOCYSTEINE[c]" NaN NaN "VAL[p]" NaN NaNNaNin theupper moundlikely means infinite.We can try to understand the less obvious ones:ADP: TODOPI: TODOPROTON[c]: presumably a measure of pHGLC[p]: glucose, this can be seen by comparingminimal.tsvwithminimal_no_glucose.tsvAMMONIUM: ammonium. This appears to be the primary source of nitrogen atoms for producing amino acids.CYTOSINE[c]: hmmm, why is external cytosine needed? Weird.
- reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/000000_basal.tsv
reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/` contains sequences of conditions for each time. For example: *contains:"time (units.s)" "nutrients" 0 "minimal"which means just usingreconstruction/ecoli/flat/condition/nutrient/minimal.tsvuntil infinity. That is the default one used byrunSim.py, as can be seen from./out/manual/wildtype_000000/000000/generation_000000/000000/simOut/Environment/attributes/nutrientTimeSeriesLabelwhich contains just000000_basal. *reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/000001_cut_glucose.tsvis more interesting and contains:so we see that this will shift the conditions half-way to a condition that will eventually kill the bacteria because it will run out of glucose and thus energy!"time (units.s)" "nutrients" 0 "minimal" 1200 "minimal_no_glucose"Timeseries can be selected with--variant nutrientTimeSeries X Y, see also: run variants.We can use that variant with:VARIANT="condition" FIRST_VARIANT_INDEX=1 LAST_VARIANT_INDEX=1 python runscripts/manual/runSim.py reconstruction/ecoli/flat/condition/condition_defs.tsvcontains lines of form:"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"]conditionrefers to entries inreconstruction/ecoli/flat/condition/condition_defs.tsvnutrientsrefers to entries underreconstruction/ecoli/flat/condition/nutrient/, e.g.reconstruction/ecoli/flat/condition/nutrient/minimal.tsvorreconstruction/ecoli/flat/condition/nutrient/minimal_plus_amino_acids.tsvgenotype perturbations: there aren't any in the file, but this suggests that genotype modifications can also be incorporated heredoubling time: TODO experimental data? Because this should be a simulation output, right? Or do they cheat and fix doubling by time?active TFs: this suggests that they are cheating transcription factors here, as those would ideally be functions of other more basic inputs
My Job is to Open and Close Doors by Mattias Pilhede (2019)
Source. An interesting humourous short meditation on common sense.In index 0,
SHT_NULL is mandatory. Are there any other uses for it: stackoverflow.com/questions/26812142/what-is-the-use-of-the-sht-null-section-in-elf ?The heart/main innovation of GitHub!
CLI hello world:
gnuplot -p -e 'p sin(x)'The default run variant, if you don't pass any options, just has the minimal growth conditions set. What this means can be seen at condition.
Notably, this implies a growth medium that includes glucose and salt. It also includes oxygen, which is not strictly required, but greatly benefits cell growth, and is of course easier to have than not have as it is part of the atmosphere!
But the medium does not include amino acids, which the bacteria will have to produce by itself.
Got it working as mentioned at: github.com/cirosantilli/feathers-chat/tree/sequelize-pg
Bibliography:
There's also a
heroku branch at: github.com/feathersjs/feathers-chat/tree/heroku, but it also seems to use NeDB? So you can have a filesystem in Heroku? Doesn't seem so: stackoverflow.com/questions/42775418/heroku-local-persistent-storageThis is a good company, first they truly helped reduce international transfer fees. They they continued to morph into a decent challenger bank.
Their Wise Interest account was amazing as of late 2023: wise.com/gb/interest/
Instant access with representative national interests and 0.29% fees.
Brick and mortar banks were way way behind in that regard!
E.g. October 2023, Wise was doing 4.87% interest after fees, while Barclay's best option was 1.16% above 5k pounds on the Rainy Day Saver (5% below). Ridiculous!
Update: On November 2023 unfortunately they more than doubled their fees from 0.19% to 0.46%:but it still was a good option to keep cash in.
These are good free newbie GUI options:
sudo apt install meld
git mergetool --tool meld
sudo apt install kdiff3
git mergetool --tool kdiff3
Let's make a more interesting conflict:
git-tips-2.sh
#!/usr/bin/env bash
set -eux
add() (
rm -f f
for i in `seq 10`; do
printf "before $i\n\n" >> f
done
printf "conflict 1 $1\n\n" >> f
for i in `seq 10`; do
printf "middle $i\n\n" >> f
done
printf "conflict 2 $2\n\n" >> f
for i in `seq 10`; do
printf "after $i\n\n" >> f
done
git add f
)
rm -rf git-tips-2
mkdir git-tips-2
cd git-tips-2
git init
for i in 1 2 3; do
add $i $i
git commit -m $i
done
add 3 4
git commit -m 4
add 5 4
git commit -m 5
git checkout HEAD~2
git checkout -b my-feature
add 3 6
git commit -m 6
add 7 6
git commit -m 7Before:
5 master
|
4 7 my-feature HEAD
| |
3 6
|/
2
|
1Action:
git rebaseAfter:Ready to push with linear history!
7 my-feature HEAD
|
6
|
5 master
|
4
|
3
|
2
|
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