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Record W2159308908 · doi:10.1016/j.jasms.2010.09.001

The extent and effects of peptide sequence scrambling via formation of macrocyclic <i>b</i> ions in model proteins

2010· article· en· W2159308908 on OpenAlexafffund
Irine S. Saminathan, X. Simon Wang, Yuzhu Guo, Olga Krakovska, Sébastien N. Voisin, Alan C. Hopkinson, K. W. Michael Siu

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoYork UniversityDeutsches Krebsforschungszentrum
KeywordsChemistryScramblingPeptideTandem mass spectrometryMass spectrometryProteomicsPeptide sequenceSequence (biology)Peptide mass fingerprintingIonChromatographyBottom-up proteomicsBiochemistryProtein mass spectrometryOrganic chemistry

Abstract

fetched live from OpenAlex

The extent and effects of sequence scrambling in peptide ions during tandem mass spectrometry (MS/MS) have been examined using tryptic peptides from model proteins. Sequence-scrambled b ions appeared in about 35% of 43 tryptic peptides examined under MS/MS conditions. In general, these ions had relatively low abundances with averages of 8% and 16%, depending on the instrumentation used. A few tryptic peptides gave abundant scrambled b ions in MS/MS. However, peptide and protein identifications under proteomic conditions with Mascot were not affected, even for these peptides wherein scrambling was prominent. From the 43 tryptic peptides that have been investigated, the conclusion is that sequence scrambling is unlikely to impact negatively on the accuracy of automated peptide and protein identifications in proteomics.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.278
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations44
Published2010
Admission routes2
Has abstractyes

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Same venueJournal of the American Society for Mass SpectrometrySame topicAdvanced Proteomics Techniques and ApplicationsFrench-language works237,207