Genomic Approaches to Studying Transcription in the Protozoan Model Tetrahymena Thermophila
Bibliographic record
Abstract
This aim of this research is to increase understanding on the process of transcription regulation using the model organism Tetrahymena thermophila. In the first aim of this research, I used the proteomic approach of affinity purification followed by mass spectrometry (AP-MS) in order to establish the conserved protein Anqa1 as a member of a MuvB-like complex in Tetrahymena. AP-MS identified high confidence interactions with Lin9 and RebL1, reinforcing the idea that these three proteins represent the core of a putative MuvB complex. AP-MS revealed interactions with other proteins such as the transcription factor MybL1, suggesting a potential formation of the activator MMB complex in Tetrahymena as seen in the interaction between MuvB and B-MYB in mammals. As part of this aim I also used Chromatin Immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) to detect Anqa1 binding sites and provide insight to its function, which helped discover a potential role of Anqa1 in transcription regulation. In the second aim of this research, to assist in the future characterization of the Mediator subunit Med31, I engineered a functional Med31-BirA* strain of Tetrahymena towards proximity labelling of Mediator associated proteins.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".