New Guidelines for Publication of Manuscripts Describing Development and Application of Targeted Mass Spectrometry Measurements of Peptides and Proteins
Notice bibliographique
Résumé
Molecular & Cellular Proteomics is pleased to announce new guidelines and requirements for papers describing the development and application of targeted mass spectrometry measurements of peptides, modified peptides and proteins (PDF). These guidelines will be implemented for papers submitted starting June, 2017. Over the past several years, representatives from academia, clinical laboratories, and pharma, who are active developers and users of targeted mass spectrometry methods and analysis tools for quantification of peptides and proteins in complex biological or clinical samples, have worked together to develop a set of guidelines and requirements for authors who want to publish targeted proteomics papers. Our goals were to define what information authors must provide regarding how such analyses were performed and the resulting data analyzed to ensure that reviewers and readers have the ability to independently establish that the measurements being reported using targeted MS methods are reliable—i.e. that they specifically identify and quantify the analytes targeted in a sample—and that the measurements are reproducible. The guidelines and requirements for authors that have been developed grew out of an NCI-sponsored meeting and subsequent publication describing a tiered, fit-for-purpose approach to targeted assay development in mass spectrometry-based proteomics (1.Carr S.A. et al.Targeted peptide measurements in biology and medicine: Best practices for mass spectrometry-based assay development using a fit-for-purpose approach.Mol. Cell. Proteomics. 2014; 13: 907-917Abstract Full Text Full Text PDF PubMed Scopus (402) Google Scholar). We have also incorporated numerous helpful and important suggestions from the community obtained during the 4-month-long public commentary period. The need for establishing guidelines for targeted MS measurements parallels the situation in discovery proteomics prior to 2004 when similar issues relating to lack of ability to ascertain reliability of published results prompted the journal Molecular & Cellular Proteomics to develop and adopt the first set of guidelines for publication of peptide and protein identification data using mass spectrometry (2.Carr S.A. Aebersold R. Baldwin M. Burlingame A. Clauser K. Nesvizhski A. The need for guidelines in publication of peptide and protein identification data.Mol. Cell. Proteomics. 2004; 3: 531-533Abstract Full Text Full Text PDF PubMed Scopus (412) Google Scholar). These guidelines, which have been repeatedly revised and updated over the past several years (3.Bradshaw R.A. Burlingame A.L. Carr S.A. Revised draft guidelines for proteomic data publication.Mol. Cell. Proteomic. 2005; 4: 1223-1225Abstract Full Text Full Text PDF PubMed Google Scholar, 4.Chalkley R.J. Clauser K.R. Carr S.A. Updating the MCP proteomic publication guidelines.ASBMB Today. 2009; : 16-17Google Scholar, 5.http://www.mcponline.org/site/misc/ms_guidelines.xhtml,Google Scholar), have been embraced in whole or in part by other journals. The goal now, as it was then, is to try to ensure that reliable and reproducible high quality data and results are entering the proteomics literature. We have endeavored to avoid making these guidelines overly prescriptive and intend to be flexible so as to allow for new technologies and approaches that will inevitably arise. We also intend to regularly revisit and revise the guidelines as needed, as we have done for our other documents for author guidance.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».