ArticleJournal of proteome research2021
Toward Comprehensive Plasma Proteomics by Orthogonal Protease Digestion.
Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 20 citations in OpenAlex.
- A genome-scale CRISPRi perturbation atlas of human induced pluripotent stem cells.Nature biotechnology · 2026Article
- Plasma proteomics for biomarker discovery in childhood tuberculosis.Nature communications · 2025Article
- Malaria exposure remodels the plasma proteome of Ghanaian children.BMC infectious diseases · 2025Article
- Protein cleaver: an interactive web interface forFrontiers in bioinformatics · 2025Article
- Instrumentation at the Leading Edge of Proteomics.Analytical chemistry · 2024Review
- Fragment ion intensity prediction improves the identification rate of non-tryptic peptides in timsTOF.Nature communications · 2024Article
- Understanding the value of biobank attributes to researchers using a conjoint experiment.Scientific reports · 2023Article
- Article
- Next-generation proteomics for quantitative Jumbophage-bacteria interaction mapping.Nature communications · 2023Article
- Overview and considerations in bottom-up proteomics.The Analyst · 2023Review
- Detergent-Assisted Protein Digestion-On the Way to Avoid the Key Bottleneck of Shotgun Bottom-Up Proteomics.International journal of molecular sciences · 2022Review
- Data-Independent Acquisition Protease-Multiplexing Enables Increased Proteome Sequence Coverage Across Multiple Fragmentation Modes.Journal of proteome research · 2022Article
- Mirror proteases of Ac-Trypsin and Ac-LysargiNase precisely improve novel event identifications inFrontiers in microbiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Rapid and consistent protein identification across large clinical cohorts is an important goal for clinical proteomics. With the development of data-independent technologies (DIA/SWATH-MS), it is now possible to analyze hundreds of samples with great reproducibility and quantitative accuracy. However, this technology benefits from empirically derived spectral libraries that define the detectable set of peptides and proteins. Here, we apply a simple and accessible tip-based workflow for the generation of spectral libraries to provide a comprehensive overview on the plasma proteome in individuals with and without active tuberculosis (TB). To boost protein coverage, we utilized nonconventional proteases such as GluC and AspN together with the gold standard trypsin, identifying more than 30,000 peptides mapping to 3309 proteins. Application of this library to quantify plasma proteome differences in TB infection recovered more than 400 proteins in 50 min of MS acquisition, including diagnostic
Indexed as
Identifiers
What 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.