Evolution of the transcriptional regulatory networks of ascomycetes
Bibliographic record
Abstract
In contrast to protein structure and to metabolic networks, an organism's transcriptional regulatory network (TRN) is highly plastic and has been reported to be the target of numerous mutations affecting the phenotype. The ascomycetes fungi are an ideal phylogenetic branch to look at TRN evolution by assessing the conservation of transcription factors (TF) and TF binding sites. In this thesis I 1) describe new tools to assess protein function in Candida albicans, 2) report a novel mode of TRN evolution that we named TF substitution that occurred in the evolution of the ribosomal protein (RP) regulon and 3) explore the large-scale transcription network reorganization of two RP TRNs with distinct wirings and TF substitutions. This work leads to a broader understanding of the span of TRN evolution at the organismal level in ascomycetes. These findings illustrate the extent of TRN plasticity in the evolution of fungi. They also raise questions regarding the rate and importance of TRN changes in the evolution of eukaryotes.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".