Using biocatalysis to integrate organic chemistry into a molecular biology laboratory course
Bibliographic record
Abstract
Current cutting-edge biomedical investigation requires that the researcher have an operational understanding of several diverse disciplines. Biocatalysis is a field of science that operates at the crossroads of organic chemistry, biochemistry, microbiology, and molecular biology, and provides an excellent model for interdisciplinary research. We have developed an inquiry-based module that uses the mutagenesis of the yeast reductase, YDL124w, to study the bioorganic synthesis of the taxol side-chain, a pharmacologically important molecule. Using related structures, students identify regions they think will affect enzyme stereoselective, design and generate site-specific mutants, and then characterize the effect of these changes on enzyme activity. This laboratory activity gives our students experience, working in a scientific discipline outside of biology and exposes them to techniques and equipment they do not normally work with in a molecular biology course. These inter-disciplinary experiences not only show the relevance of other sciences to biology, but also give our students the ability to communicate more effectively with scientists outside their discipline.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".