Using OrthoCluster for the Detection of Synteny Blocks Among Multiple Genomes
Bibliographic record
Abstract
Synteny blocks are composed of two or more orthologous genes conserved among species, resulting from speciation from their last common ancestor. OrthoCluster (Zeng et al., 2008) is a fast and easy-to-use program for the identification of synteny blocks among multiple genomes. It allows users to identify synteny blocks that contain different types of mismatches, and to decide whether they require conservation of gene orientation and conservation of gene order within the blocks. OrthoCluster can also be used to find duplicated blocks within genomes. Although genes and their correspondence are usually used as input for OrthoCluster, in fact, OrthoCluster can be applied using any type of markers as input as long as their relationships can be established. OrthoClusterDB provides a Web interface for running OrthoCluster with user-defined datasets and parameters, as well as for browsing and downloading precomputed synteny blocks for different groups of genomes.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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".