MetaBridge: An Integrative Multi‐Omics Tool for Metabolite‐Enzyme Mapping
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
MetaBridge is a web-based tool designed to facilitate the integration of metabolomics with other "omics" data types such as transcriptomics and proteomics. It uses data from the MetaCyc metabolic pathway database and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to map metabolite compounds to directly interacting upstream or downstream enzymes in enzymatic reactions and metabolic pathways. The resulting list of enzymes can then be integrated with transcriptomics or proteomics data via protein-protein interaction networks to perform integrative multi-omics analyses. MetaBridge was developed to be intuitive and easy to use, requiring little to no prior computational experience. The protocols described here detail all steps involved in the use of MetaBridge, from preparing input data and performing metabolite mapping to utilizing the results to build a protein-protein interaction network. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Mapping metabolite data using MetaCyc identifiers Basic Protocol 2: Mapping metabolite data using KEGG identifiers Support Protocol 1: Converting compound names to HMDB IDs Support Protocol 2: Submitting mapped genes produced by MetaBridge for protein-protein interaction (PPI) network construction.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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 it