Thermodynamics of Oligonucleotide Duplex Melting
Bibliographic record
Abstract
Melting temperatures of oligonucleotides are useful for a number of molecular biology applications, such as the polymerase chain reaction (PCR). Although melting temperatures are often calculated with simplistic empirical equations, application of thermodynamics provides more accurate melting temperatures and an opportunity for students to apply rigorous thermodynamic analysis to an important biochemical problem. Because the stacking of base pairs on top of one another is a significant factor in the energetics of oligonucleotide melting, several investigators have applied van't Hoff analysis to melting temperature data using a nearest-neighbor model and have obtained entropies and enthalpies for the stacking of bases. The present article explains how the equilibrium constant for the dissociation of strands from double-stranded oligonucleotides can be expressed in terms of the total strand concentration and thus how the total strand concentration influences the melting temperature. It also presents a simplified analysis based on the entropies and enthalpies of stacking that is manually tractable so that students can work examples to help them understand the thermodynamics of oligonucleotide melting.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".