Symmetry observations in long nucleotide sequences: a commentary on the Discovery Note of Qi and Cuticchia
Bibliographic record
Abstract
The relative quantities of bases in DNA were determined chemically many years before sequencing technologies permitted direct counting of bases. Apparently unaware of the rich literature on the topic, bioinformaticists are today rediscovering the 'wheels' of Chargaff, Wyatt and other biochemists. It follows from Chargaff's second parity rule (%A = %T, %G = %C for single stranded DNA) that the symmetries observed for the two pairs of complementary mononucleotide bases, should also apply to the eight pairs of complementary dinucleotide bases, the thirty-two pairs of complementary trinucleotide bases, etc. This was made explicit by Prabhu in 1993 in a study of complete genomes and long genome segments from a wide range of taxa, and was rediscovered by Qi and Cuticchia in 2001 in a study of complete genomes. It follows from Chargaff's GC-rule (%GC tends to be uniform and species specific) that, within a species, oligonucleotides of the same GC% will be at approximately equal quantities in single stranded DNA. Thus, for example, while quantities of CAT and ATG (reverse complements) will be closely correlated because of both of the above Chargaff rules, CAT and GTA (forward complements) will show some correlation only because of the latter rule. The need for complete genomic sequences in bioinformatic analyses may have been somewhat overplayed.
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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 | 0.023 | 0.067 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.008 | 0.023 |
| Open science | 0.012 | 0.005 |
| Research integrity | 0.035 | 0.091 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".