Applications of Recombinant Dna Technology in Gastrointestinal Medicine and Hepatology: Basic Paradigms of Molecular Cell Biology. Part B: Eukaryotic Gene Transcription and Post-Transcripional Rna Processing
Bibliographic record
Abstract
The transcription of DNA into RNA is the primary level at which gene expression is controlled in eukaryotic cells. Eukaryotic gene transcription involves several different RNA polymerases that interact with a host of transcription factors to initiate transcription. Genes that encode proteins are transcribed into messenger RNA (mRNA) by RNA polymerase II. Ribosomal RNAs (rRNAs) and transfer RNAs (tRNAs) are transcribed by RNA polymerase I and III, respectively. The production of each mRNA in human cells involves complex interactions of proteins (ie, trans-acting factors) with specific sequences on the DNA (ie, cis-acting elements). Cis-acting elements are short base sequences adjacent to or within a particular gene. While the regulation of transcription is a pivotal step in the control of gene expression, a variety of molecular events, collectively known as 'RNA processing' add an additional level of control of gene expression in eukaryotic cells. (Pour le résumé, voir page suivante)
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
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".