ArticleMethods in molecular biology (Clifton, N.J.)2022
Review of the Real and Sometimes Hidden Costs in Proteomics Experimental Workflows.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.Journal of medicinal chemistry · 2026Review
- Appraisal of the Use of Proteomics Methodological Approaches and Technologies on Sheep and Goat Research and Clinical Work.Animals : an open access journal from MDPI · 2025Article
- The $10 proteome: low-cost, deep and quantitative proteome profiling of limited sample amounts using the Orbitrap Astral and timsTOF Ultra 2 mass spectrometers.bioRxiv : the preprint server for biology · 2025Article
- Mass Spectrometry Advancements and Applications for Biomarker Discovery, Diagnostic Innovations, and Personalized Medicine.International journal of molecular sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A typical proteomics workflow covers all the steps from growing or collecting the cells/tissues/organism, protein extraction, digestion and cleanup, mass spectrometric analysis, and, finally, extensive bioinformatics to derive biological insight from the data. The details of the procedures employed for this can vary widely by laboratory and by sample type: e.g., hard tissues or cells with walls require much more mechanical disruption to extract proteins than do soft tissues, biological fluids, or wall-less cells. Everything then converges on the mass spectrometer, where there are further choices to be made about how to do the analysis. There is one commonality, however, virtually every group around the world now uses liquid chromatography on-line coupled to tandem mass spectrometry, which means that significant amounts of instrument time are dedicated to every sample. There are many other reviews or methods papers, including in this volume, that cover the details of the various procedures involved in proteomic analyses of all types of samples. Our focus here will be on the cost considerations for such analyses, including considerations to ensure that useful data can be obtained the first time a sample is analyzed. Some of these costs are often overlooked, particularly for those groups who operate their own mass spectrometer(s) and do not have to go to a fee-for-service facility to have something analyzed. The chapter presents several challenges and key suggestions in proving hypotheses in proteomics experimental workflow in different biological systems with specific regard to the costs involved, both real and hidden. The detailed methodology for cost-based studies reported in this chapter can help researchers to set up their laboratory with appropriate equipment as well as to identify potential collaborations based on their analytical instrumentation.
Indexed as
Identifiers
35612731What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.