ECMDB: The E. coli Metabolome Database
Bibliographic record
Abstract
The Escherichia coli Metabolome Database (ECMDB, http://www.ecmdb.ca) is a comprehensively annotated metabolomic database containing detailed information about the metabolome of E. coli (K-12). Modelled closely on the Human and Yeast Metabolome Databases, the ECMDB contains >2600 metabolites with links to ∼1500 different genes and proteins, including enzymes and transporters. The information in the ECMDB has been collected from dozens of textbooks, journal articles and electronic databases. Each metabolite entry in the ECMDB contains an average of 75 separate data fields, including comprehensive compound descriptions, names and synonyms, chemical taxonomy, compound structural and physicochemical data, bacterial growth conditions and substrates, reactions, pathway information, enzyme data, gene/protein sequence data and numerous hyperlinks to images, references and other public databases. The ECMDB also includes an extensive collection of intracellular metabolite concentration data compiled from our own work as well as other published metabolomic studies. This information is further supplemented with thousands of fully assigned reference nuclear magnetic resonance and mass spectrometry spectra obtained from pure E. coli metabolites that we (and others) have collected. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of E. coli's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers but also to molecular biologists, systems biologists and individuals in the biotechnology industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".