Identifying Genes Regulated in a Myc-dependent Manner
Bibliographic record
Abstract
The c-myc proto-oncogene can direct a diverse array of biological activities, including cell cycle progression, apoptosis, and differentiation. It is believed that Myc can affect this wide variety of activities by functioning as a regulator of gene transcription, although few targets have been identified to date. To delineate the molecular program regulated downstream of Myc, we used a cDNA microarray approach and identified 52 putative targets out of >6000 cDNAs analyzed. To further distinguish the subset of genes whose regulation was dependent upon Myc per se from those regulated in response to activation of general mitogenic or apoptotic programs, the putative cDNA targets were then screened by a series of assays. By this approach 37 putative targets were ruled out and 15 Myc target genes were uncovered. Interestingly, comparing our results with other high throughput screens reveals that certain putative Myc targets previously reported are shown not to be regulated downstream of Myc (e.g. ribosomal proteins, HSP90beta), whereas others are further supported by our analyses (e.g. pdgfbetar, nucleolin). The identity of genes specifically regulated downstream of Myc provides the critical tools required to understand the role Myc holds in the transformation process and to delineate how Myc functions as a regulator of gene transcription.
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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 | 0.000 | 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) | 0.001 | 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".