Integrated and Sequence-Ordered BAC- and YAC-Based Physical Maps for the Rat Genome
Bibliographic record
Abstract
As part of the effort to sequence the genome of Rattus norvegicus, we constructed a physical map comprised of fingerprinted bacterial artificial chromosome (BAC) clones from the CHORI-230 BAC library. These BAC clones provide approximately 13-fold redundant coverage of the genome and have been assembled into 376 fingerprint contigs. A yeast artificial chromosome (YAC) map was also constructed and aligned with the BAC map via fingerprinted BAC and P1 artificial chromosome clones (PACs) sharing interspersed repetitive sequence markers with the YAC-based physical map. We have annotated 95% of the fingerprint map clones in contigs with coordinates on the version 3.1 rat genome sequence assembly, using BAC-end sequences and in silico mapping methods. These coordinates have allowed anchoring 358 of the 376 fingerprint map contigs onto the sequence assembly. Of these, 324 contigs are anchored to rat genome sequences localized to chromosomes, and 34 contigs are anchored to unlocalized portions of the rat sequence assembly. The remaining 18 contigs, containing 54 clones, still require placement. The fingerprint map is a high-resolution integrative data resource that provides genome-ordered associations among BAC, YAC, and PAC clones and the assembled sequence of the rat genome.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".