Let's try to understand some interesting looking, with a special focus on our understanding of the tiny E. Coli K-12 MG1655 operon thrLABC part of the metabolism, which we have well understood at Section "E. Coli K-12 MG1655 operon thrLABC".
reconstruction/ecoli/flat/compartments.tsvcontains cellular compartment information:"abbrev" "id" "n" "CCO-BAC-NUCLEOID" "j" "CCO-CELL-PROJECTION" "w" "CCO-CW-BAC-NEG" "c" "CCO-CYTOSOL" "e" "CCO-EXTRACELLULAR" "m" "CCO-MEMBRANE" "o" "CCO-OUTER-MEM" "p" "CCO-PERI-BAC" "l" "CCO-PILUS" "i" "CCO-PM-BAC-NEG"CCO: "Celular COmpartment"BAC-NUCLEOID: nucleoidCELL-PROJECTION: cell projectionCW-BAC-NEG: TODO confirm: cell wall (of a Gram-negative bacteria)CYTOSOL: cytosolEXTRACELLULAR: outside the cellMEMBRANE: cell membraneOUTER-MEM: bacterial outer membranePERI-BAC: periplasmPILUS: pilusPM-BAC-NEG: TODO: plasma membrane, but that is the same as cell membrane no?
reconstruction/ecoli/flat/promoters.tsvcontains promoter information. Simple file, sample lines:corresponds to E. Coli K-12 MG1655 promoter thrLp, which starts as position 148."position" "direction" "id" "name" 148 "+" "PM00249" "thrLp"reconstruction/ecoli/flat/proteins.tsvcontains protein information. Sample line corresponding to e. Coli K-12 MG1655 gene thrA:so we understand that:"aaCount" "name" "seq" "comments" "codingRnaSeq" "mw" "location" "rnaId" "id" "geneId" [91, 46, 38, 44, 12, 53, 30, 63, 14, 46, 89, 34, 23, 30, 29, 51, 34, 4, 20, 0, 69] "ThrA" "MRVL..." "Location information from Ecocyc dump." "AUGCGAGUGUUG..." [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 89103.51099999998, 0.0, 0.0, 0.0, 0.0] ["c"] "EG10998_RNA" "ASPKINIHOMOSERDEHYDROGI-MONOMER" "EG10998"aaCount: amino acid count, how many of each of the 20 proteinogenic amino acid are thereseq: full sequence, using the single letter abbreviation of the proteinogenic amino acidsmw; molecular weight? The 11 components appear to be given atreconstruction/ecoli/flat/scripts/unifyBulkFiles.py:so they simply classify the weight? Presumably this exists for complexes that have multiple classes?molecular_weight_keys = [ '23srRNA', '16srRNA', '5srRNA', 'tRNA', 'mRNA', 'miscRNA', 'protein', 'metabolite', 'water', 'DNA', 'RNA' # nonspecific RNA ]23srRNA,16srRNA,5srRNAare the three structural RNAs present in the ribosome: 23S ribosomal RNA, 16S ribosomal RNA, 5S ribosomal RNA, all others are obvious:- tRNA
- mRNA
- protein. This is the seventh class, and this enzyme only contains mass in this class as expected.
- metabolite
- water
- DNA
- RNA: TODO
rnavsmiscRNA
location: cell compartment where the protein is present,cdefined atreconstruction/ecoli/flat/compartments.tsvas cytoplasm, as expected for something that will make an amino acid
reconstruction/ecoli/flat/rnas.tsv: TODO vstranscriptionUnits.tsv. Sample lines:"halfLife" "name" "seq" "type" "modifiedForms" "monomerId" "comments" "mw" "location" "ntCount" "id" "geneId" "microarray expression" 174.0 "ThrA [RNA]" "AUGCGAGUGUUG..." "mRNA" [] "ASPKINIHOMOSERDEHYDROGI-MONOMER" "" [0.0, 0.0, 0.0, 0.0, 790935.00399999996, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] ["c"] [553, 615, 692, 603] "EG10998_RNA" "EG10998" 0.0005264904halfLife: half-lifemw: molecular weight, same as inreconstruction/ecoli/flat/proteins.tsv. This molecule only have weight in themRNAclass, as expected, as it just codes for a proteinlocation: same as inreconstruction/ecoli/flat/proteins.tsvntCount: nucleotide count for each of the ATGCmicroarray expression: presumably refers to DNA microarray for gene expression profiling, but what measure exactly?
reconstruction/ecoli/flat/sequence.fasta: FASTA DNA sequence, first two lines:>E. coli K-12 MG1655 U00096.2 (1 to 4639675 = 4639675 bp) AGCTTTTCATTCTGACTGCAACGGGCAATATGTCTCTGTGTGGATTAAAAAAAGAGTGTCTGATAGCAGCTTCTGreconstruction/ecoli/flat/transcriptionUnits.tsv: transcription units. We can observe for example the two different transcription units of the E. Coli K-12 MG1655 operon thrLABC in the lines:"expression_rate" "direction" "right" "terminator_id" "name" "promoter_id" "degradation_rate" "id" "gene_id" "left" 0.0 "f" 310 ["TERM0-1059"] "thrL" "PM00249" 0.198905992329492 "TU0-42486" ["EG11277"] 148 657.057317358791 "f" 5022 ["TERM_WC-2174"] "thrLABC" "PM00249" 0.231049060186648 "TU00178" ["EG10998", "EG10999", "EG11000", "EG11277"] 148promoter_id: matches promoter id inreconstruction/ecoli/flat/promoters.tsvgene_id: matches id inreconstruction/ecoli/flat/genes.tsvid: matches exactly those used in BioCyc, which is quite nice, might be more or less standardized:
reconstruction/ecoli/flat/genes.tsv"length" "name" "seq" "rnaId" "coordinate" "direction" "symbol" "type" "id" "monomerId" 66 "thr operon leader peptide" "ATGAAACGCATT..." "EG11277_RNA" 189 "+" "thrL" "mRNA" "EG11277" "EG11277-MONOMER" 2463 "ThrA" "ATGCGAGTGTTG" "EG10998_RNA" 336 "+" "thrA" "mRNA" "EG10998" "ASPKINIHOMOSERDEHYDROGI-MONOMER"reconstruction/ecoli/flat/metabolites.tsvcontains metabolite information. Sample lines:In the case of the enzyme thrA, one of the two reactions it catalyzes is "L-aspartate 4-semialdehyde" into "Homoserine"."id" "mw7.2" "location" "HOMO-SER" 119.12 ["n", "j", "w", "c", "e", "m", "o", "p", "l", "i"] "L-ASPARTATE-SEMIALDEHYDE" 117.104 ["n", "j", "w", "c", "e", "m", "o", "p", "l", "i"]Starting from the enzyme page: biocyc.org/gene?orgid=ECOLI&id=EG10998 we reach the reaction page: biocyc.org/ECOLI/NEW-IMAGE?type=REACTION&object=HOMOSERDEHYDROG-RXN which has reaction IDHOMOSERDEHYDROG-RXN, and that page which clarifies the IDs:so these are the compounds that we care about.- biocyc.org/compound?orgid=ECOLI&id=L-ASPARTATE-SEMIALDEHYDE: "L-aspartate 4-semialdehyde" has ID
L-ASPARTATE-SEMIALDEHYDE - biocyc.org/compound?orgid=ECOLI&id=HOMO-SER: "Homoserine" has ID
HOMO-SER
- biocyc.org/compound?orgid=ECOLI&id=L-ASPARTATE-SEMIALDEHYDE: "L-aspartate 4-semialdehyde" has ID
reconstruction/ecoli/flat/reactions.tsvcontains chemical reaction information. Sample lines:"reaction id" "stoichiometry" "is reversible" "catalyzed by" "HOMOSERDEHYDROG-RXN-HOMO-SER/NAD//L-ASPARTATE-SEMIALDEHYDE/NADH/PROTON.51." {"NADH[c]": -1, "PROTON[c]": -1, "HOMO-SER[c]": 1, "L-ASPARTATE-SEMIALDEHYDE[c]": -1, "NAD[c]": 1} false ["ASPKINIIHOMOSERDEHYDROGII-CPLX", "ASPKINIHOMOSERDEHYDROGI-CPLX"] "HOMOSERDEHYDROG-RXN-HOMO-SER/NADP//L-ASPARTATE-SEMIALDEHYDE/NADPH/PROTON.53." {"NADPH[c]": -1, "NADP[c]": 1, "PROTON[c]": -1, "L-ASPARTATE-SEMIALDEHYDE[c]": -1, "HOMO-SER[c]": 1 false ["ASPKINIIHOMOSERDEHYDROGII-CPLX", "ASPKINIHOMOSERDEHYDROGI-CPLX"]catalized by: here we seeASPKINIHOMOSERDEHYDROGI-CPLX, which we can guess is a protein complex made out ofASPKINIHOMOSERDEHYDROGI-MONOMER, which is the ID for thethrAwe care about! This is confirmed incomplexationReactions.tsv.
reconstruction/ecoli/flat/complexationReactions.tsvcontains information about chemical reactions that produce protein complexes:The"process" "stoichiometry" "id" "dir" "complexation" [ { "molecule": "ASPKINIHOMOSERDEHYDROGI-CPLX", "coeff": 1, "type": "proteincomplex", "location": "c", "form": "mature" }, { "molecule": "ASPKINIHOMOSERDEHYDROGI-MONOMER", "coeff": -4, "type": "proteinmonomer", "location": "c", "form": "mature" } ] "ASPKINIHOMOSERDEHYDROGI-CPLX_RXN" 1coeffis how many monomers need to get together for form the final complex. This can be seen from the Summary section of ecocyc.org/gene?orgid=ECOLI&id=ASPKINIHOMOSERDEHYDROGI-MONOMER:Fantastic literature summary! Can't find that in database form there however.Aspartate kinase I / homoserine dehydrogenase I comprises a dimer of ThrA dimers. Although the dimeric form is catalytically active, the binding equilibrium dramatically favors the tetrameric form. The aspartate kinase and homoserine dehydrogenase activities of each ThrA monomer are catalyzed by independent domains connected by a linker region.
reconstruction/ecoli/flat/proteinComplexes.tsvcontains protein complex information:"name" "comments" "mw" "location" "reactionId" "id" "aspartate kinase / homoserine dehydrogenase" "" [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 356414.04399999994, 0.0, 0.0, 0.0, 0.0] ["c"] "ASPKINIHOMOSERDEHYDROGI-CPLX_RXN" "ASPKINIHOMOSERDEHYDROGI-CPLX"reconstruction/ecoli/flat/protein_half_lives.tsvcontains the half-life of proteins. Very few proteins are listed however for some reason.reconstruction/ecoli/flat/tfIds.csv: transcription factors information:"TF" "geneId" "oneComponentId" "twoComponentId" "nonMetaboliteBindingId" "activeId" "notes" "arcA" "EG10061" "PHOSPHO-ARCA" "PHOSPHO-ARCA" "fnr" "EG10325" "FNR-4FE-4S-CPLX" "FNR-4FE-4S-CPLX" "dksA" "EG10230"
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"
The language all browsers converted to as of 2019, and therefore the easiest one to distribute and most widely implemented programming language.
Hopefully will be killed by WebAssembly one day.
Because JavaScript is a relatively crap/ad-hoc language, it ended up some decent tooling to make up for that, e.g. stuff like linting via ESLint and reformatting through Prettier is much more widespread than in other languages.
JavaScript data structure are also quite a bit anemic, which makes libraries such as lodash incredibly popular. But most of that stuff should be in the stdlib.
Our JavaScript examples can be found at:
- Node.js example: examples that don't interact with any browser feature. We are just testing those on the CLI which is much more convenient.
- JavaScript browser example: examples that interact with browser-specific features, notably the DOM
Tried a quick port to SQLite to get rid of annoying local databases for development, but failed, at c1c2cc4e448b279ff083272df1ac50d20c3304faandthen:fails with:Attempt to hack it:and after that it seems to run.
npm install sqlite3 --save-dev{
"type": "sqlite",
"database": "db.sqlite3",
"entities": ["src/**/**.entity{.ts,.js}"],
"synchronize": true
}npm startDataTypeNotSupportedError: Data type "timestamp" in "ArticleEntity.created" is not supported by "sqlite" database.--- a/src/article/article.entity.ts
+++ b/src/article/article.entity.ts
@@ -20,10 +20,10 @@ export class ArticleEntity {
@Column({default: ''})
body: string;
- @Column({ type: 'timestamp', default: () => "CURRENT_TIMESTAMP"})
+ @Column({ default: () => "CURRENT_TIMESTAMP"})
created: Date;
- @Column({ type: 'timestamp', default: () => "CURRENT_TIMESTAMP"})
+ @Column({ default: () => "CURRENT_TIMESTAMP"})
updated: Date;I can signup and login, terrible error reporting as usual, make sure to use long enough usernames/passwords.
However, article creation fails with:
Unhandled Rejection (TypeError): Cannot read property 'slug' of undefinedHow many stupid bugs. How many stupid bugs do we need to face???
- this fucking train-wreck cannot come up with a unified documented way of specifying dependencies:So basically
- stackoverflow.com/questions/14399534/reference-requirements-txt-for-the-install-requires-kwarg-in-setuptools-setup-py
- stackoverflow.com/questions/26900328/install-dependencies-from-setup-py
- stackoverflow.com/questions/30797124/how-to-use-setup-py-to-install-dependencies-only/63743115
- stackoverflow.com/questions/6947988/when-to-use-pip-requirements-file-versus-install-requires-in-setup-py
requirements.txtis thepackage-lock.json. But how to generate it cleanly? You would need to create a virtualenv? pip searchwas disabled in 2020: stackoverflow.com/questions/17373473/how-do-i-search-for-an-available-python-package-using-pip. WTF. If server load is a problem, just create a token system! It is hard to understand how such a popular language can't raise enough money to keep such simple server functionality running.
Based on JCVI-syn3.0, they've added a few genes back to give better phenotypes, including slightly faster duplication time. Because the development cycle time is your God is also true in biology.
As of essential metabolism for a minimal cell (2019) it had only 91 genes of unknown function! So funny.
Bibliograpy:
Our notation: , called "dihedral group of degree n", means the dihedral group of the regular polygon with sides, and therefore has order (all rotations + flips), called the "dihedral group of order 2n".
This web framework is pretty good as of 2020 compared to others, because it managed to gain a critical community size, and there's a lot of basic setup already done for you.
it is just big shame it wasn't written in Python or even better, Node.js, because learning Ruby is completely useless for anything else. As of 2020 for example, most Node.js web frameworks feel like crap compared to Rails, you just have to debug so much there.
Used in GitLab, which is why Ciro Santilli touched it.
Integrations React integration:
- github.com/shakacode/react_on_rails: webpack and server-side rendering
- github.com/reactjs/react-rails Official on the React side only. Demo app linked from package: github.com/BookOfGreg/react-rails-example-app and how it fails: github.com/BookOfGreg/react-rails-example-app/issues/30... The related projects section has some good links:
- shakacode/react_on_rails
- github.com/hyperstack-org/hyperstack transpiles Ruby to JavaScript + React. What could possibly go wrong? :-)
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 3. Visual Studio Code extension installation.
Figure 4. Visual Studio Code extension tree navigation.
Figure 5. Web editor. 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.Video 4. OurBigBook Visual Studio Code extension editing and navigation demo. Source. 
- 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