Bibliographic record
Abstract
While bioconjugation involves the fusion of two biomolecules, for example protein-protein, polymerprotein, carbohydrate-protein conjugates, it also involves the attachment of synthetic labels (isotope labels, fluorescent dyes, affinity tags, biotin) to biological entities such as carbohydrates, proteins, peptides, synthetic polymers, enzymes, glycans, antibodies, nucleic acids, and oligonucleotides (ONTs). This chapter provides a comprehensive review of the different types of covalent and noncovalent bioconjugation methods such as carboxyl modifications, amine modifications, thiol modifications, biotin-(strept)avidin system, electrostatic interactions, and metal-mediated non-covalent conjugation, available for the modification of biomolecules (proteins, peptides, carbohydrates, polymers, DNA). Traditional bioconjugation methods are first elaborated upon, followed by some modern bioconjugation techniques, particularly the emerging role of bioorthogonal chemistry, where the translation of knowledge of chemical reactions to reactions in living systems can be achieved. While the synthetic aspects of the bioconjugates are the main focus, a brief description of their applications is also presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.052 | 0.001 |
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; both teacher heads agree on what is shown here.
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".