Multifunctional zinc finger proteins in development and disease
Bibliographic record
Abstract
Post-transcriptional processes contribute significantly towards the generation of proteomic diversity. An increasing number of mutations have been described that affect genes encoding components of the post-transcriptional machinery. In particular, multifunctional proteins that link transcription with post-transcriptional processes have been implicated in several human diseases including cancer. A predominant feature of these proteins is the zinc finger, an ancient structural motif that mediates protein ratio protein interactions and is capable of interacting with both DNA and RNA. Zinc finger proteins are the most abundant class of proteins in the human proteome, yet the majority remain uncharacterised. Here we describe multifunctional zinc finger proteins linked to human development and disease. The examples discussed are WT1, ZNF74, EWS, TLS, TAFII68, YY1, CTCF and the GLI proteins. The study of these and other zinc finger proteins provides insights into the functional versatility of the zinc finger motif and suggests that both alternative splicing and sub-cellular compartmentalisation may modulate their multifunctionality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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 | 0.003 |
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".