Abstracts of keynote & plenary lectures
Bibliographic record
Abstract
Identification of the secondary structure responsible for peptide biology is of academic interest to characterize natural modes of action, as well as industrially relevant for the development of peptide mimics.Traditionally, such scanning of peptide structure has been performed by systematic replacement of each residue in the peptide sequence with another proteinogenic amino acid.For example, alanine, enantiomeric amino acid and proline scans have been respectively performed to study the importance of side chains, stereochemistry and conformation on the biological activity of the peptide.Our lab has been developing alternative scanning methods for characterizing the relationship between peptide structure and activity.For example, we have recently introduced effective solid-phase methods for introducing aza-amino acid residues systematically at different positions along the peptide chain.Because aza-amino acid residues have been shown to adopt the i ϩ 1 and i ϩ 2 positions of beta-turns, aza-amino acid scanning offers potential for identifying regions of turn secondary structure which are important for biology.Similarly, we are pursuing solid-phase chemistry for introducing lactam constraints at different positions along the peptide.Our presentation will focus on recent achievements in the development of new methodology for scanning various peptide sequences to identify secondary structures relevant for biological activity.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.378 | 0.288 |
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".