In Vivo Analysis of Ribonucleoprotein Complexes Using Nucleotide Analog Interference Mapping
Bibliographic record
Abstract
Multicomponent RNA-protein complexes are essential for eukaryotic gene expression. Some, like the spliceosome, have been studied successfully in vitro using biochemical and structural approaches, but many have not been reconstituted in cell-free systems. Nucleotide analog interference mapping (NAIM) can report detailed atomic information about requirements for ribonucleoprotein particle assembly and function in living cells, providing a method to study complexes in a cellular context at a level of detail comparable to many biochemical assays. The method relies on incorporation of phosphorothioate-tagged nucleotide analogs during in vitro transcription, followed by a selection for the active population of molecules and analysis of the selected RNA sequence composition. Xenopus oocytes provide a cellular environment for selecting active molecules based on particle assembly or function. Functional group analysis of complexes assembled in vivo provides predictive models for further investigation either in vivo or in vitro as well as benchmarks for evaluating and refining biochemical and structural models.
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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".