Proteomics Propels Protein Degradation Studies in San Diego
Bibliographic record
Abstract
Exquisite in vitro biochemical examinations of protein ubiquitylation and degradation have historically been the dominant methods for unraveling the mechanisms of protein destruction. The study of protein abundance alterations and protein modifications, a cornerstone of protein degradation pathways, naturally lends itself to global and systematic proteomic methods to decipher the emerging complexity of protein degradation pathways. Advances in proteomic technologies have fueled an explosion of systematic and quantitative studies aimed at understanding how the proteome is shaped and regulated by ubiquitin-dependent processes. These types of studies, as well as targeted analyses of cellular pathways, have revealed that alterations in protein degradation function can have a severe impact on human health and disease. The fusion of these two themes was the focus of the January 2012 conference on proteomics of protein degradation and ubiquitin pathways (PPDUP) held in San Diego. To gain insights into both the current state-of-the-art proteomic methods to investigate protein turnover, and how protein degradation function is altered within a range of human disorders a variety of speakers revealed the many connections between altered protein degradation function and human disease. Many of the sessions were framed by a consistent focus aimed at the discovery and development of novel therapeutics targeting protein degradation pathway components to treat various human maladies ranging from cancer to heart disease.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.102 | 0.068 |
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".