<i>Fox</i>gene loci in<i>Takifugu rubripes</i>and<i>Tetraodon nigroviridis</i>genomes and comparison with those of medaka and zebrafish genomes
Bibliographic record
Abstract
Members of the Fox gene family of transcriptional regulators are essential for animal development and have been extensively studied in vertebrates. The mouse and human genomes contain at least 40 FOX genes which are divided into 19 subclasses based on the sequence similarity of the highly conserved forkhead domain. Using the genome sequence of the Takifugu rubripes and Tetraodon nigroviridis , we examined the genomic complement of fox genes in these organisms to gain insight into the evolutionary relationship of this gene family. We identified 53 fox genes in Tetraodon nigroviridis and Takifugu rubripes genome by searching the forkhead domain. These genes are divided into 18 subclasses as follows: 8 fox genes in subclass O; 6 in subclass P ; 4 in subclasses D, J, and N; 3 in subclasses A, B, C, E, F, and I; 2 in subclasses K, L, and Q; and 1 in subclasses G, H, M, and R. Together with the forkhead domain sequences of human, chicken, frog, zebrafish, medaka, and Caenorhabditis elegans, the phylogenetic relationship of the fox genes in Takifugu rubripes and Tetraodon nigroviridis were analyzed and compared. The genes structure, general features, and the three-dimensional model of these genes were also discussed.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".