Probe my Pathway (PmP): a portal to explore the chemical coverage of the human Reactome
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
Deciphering pathway-phenotype associations is critical for a system-wide understanding of cells and the chemistry of life. An approach to reach this goal is to systematically modulate pathways pharmacologically. The targeted and controlled regulation of an increasing number of proteins is becoming possible, thanks to the growing list of chemical probes and chemogenomic compounds available to cell biologists, but no resource is available that directly maps these chemical tools on cellular pathways. To fill this gap, we developed Probe my Pathway (PmP), a database where high-quality chemical probes and well-characterized sets of chemogenomic compounds are mapped on all the human pathways of the Reactome database. The web interface allows users to browse the data via icicle charts or search the data for compounds, proteins, or pathways. Chemists can rapidly find pathways with low chemical coverage or explore the structural chemistry of ligands targeting specific cellular machineries. Cell biologists can look for chemical probes targeting different proteins in the same pathway or find which pathways are targeted by chemical probes of interest. PmP is updated annually and will grow with the expanding chemical tool kit produced by Target 2035 and other efforts. Database URL: https://apps.thesgc.org/pmp/.
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.
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 | 0.000 |
| 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