Quantitative Proteomic Analysis Using a MALDI Quadrupole Time-of-Flight Mass Spectrometer
Bibliographic record
Abstract
We describe an approach to the quantitative analysis of complex protein mixtures using a MALDI quadrupole time-of-flight (MALDI QqTOF) mass spectrometer and isotope coded affinity tag reagents (Gygi, S. P.; et al. Nat. Biotechnol. 1999, 17, 994-9.). Proteins in mixtures are first labeled on cysteinyl residues using an isotope coded affinity tag reagent, the proteins are enzymatically digested, and the labeled peptides are purified using a multidimensional separation procedure, with the last step being the elution of the labeled peptides from a microcapillary reversed-phase liquid chromatography column directly onto a MALDI sample target. After addition of matrix, the sample spots are analyzed using a MALDI QqTOF mass spectrometer, by first obtaining a mass spectrum of the peptides in each sample spot in order to quantify the ratio of abundance of pairs of isotopically tagged peptides, followed by tandem mass spectrometric analysis to ascertain the sequence of selected peptides for protein identification. The effectiveness of this approach is demonstrated in the quantification and identification of peptides from a control mixture of proteins of known relative concentrations and also in the comparative analysis of protein expression in Saccharomyces cerevisiae grown on two different carbon sources.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".