Functional proteomic approaches for the analysis of a dynamic signaling pathway
Bibliographic record
Abstract
The long-term challenge of proteomics as a tool for systems biology is to define the identities, quantities, structures and functions of complete complements of proteins, and to characterize how these properties vary in different cellular environments. To add a functional dimension to the dynamic TGFbeta network revealed by the LUMIER screen, a recently developed and validated high throughput technology for analysis of dynamic protein interactions in mammalian cells, I have used functional assays based on Smad transcriptional responses. Novel pathway inhibitors, including an uncharacterized protein FLJ12604, two WW domain-containing proteins WWP2, TAZ as well as PP2A regulatory subunit PPP2R2D were identified. To facilitate analysis of distinct subnetworks within the TGFbeta interactome, I have also worked towards developing a mass spectrometry (MS)-based approach to study dynamics of protein complex assembly in a quantitative manner. Taken together, LUMIER coupled with the MS technology can be used to study crucial, although previously unexplored, dimensions of signaling pathways.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".