ArticleBioinformatics (Oxford, England)2020
The use of missing values in proteomic data-independent acquisition mass spectrometry to enable disease activity discrimination.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 38 citations in OpenAlex.
- Transitioning from Transcriptomics to Proteomics: Enhancing Mechanistic Accuracy in PBPK Modeling via Absolute Protein Abundances.CPT: pharmacometrics & systems pharmacology · 2026Article
- Enabling cross-indication protein expression analysis using a curated pan-cancer dataset and a tailored workflow.Scientific reports · 2026Article
- Optimization of protein extraction and digestion workflows for proteomic analysis of saliva, salivary stones and kidney stones.Frontiers in molecular biosciences · 2026Article
- The Selective Bromodomain and Extra-Terminal Domain (BET) Inhibitor RVX-208 Reduces Cocaine-Seeking Behaviour and Alters Proteomic Pathways in the Nucleus Accumbens.Addiction biology · 2026Article
- Mapping the complexity of ME/CFS: Evidence for abnormal energy metabolism, altered immune profile, and vascular dysfunction.Cell reports. Medicine · 2025Article
- Proteomic profiling of human plasma and intervertebral disc tissue reveals matrisomal, but not plasma, biomarkers of disc degeneration.Arthritis research & therapy · 2025Article
- Proteomic Characterization of Plasma in Lemierre's Syndrome.Thrombosis and haemostasis · 2024Article
- Proteomic changes induced by longevity-promoting interventions in mice.GeroScience · 2024Article
- Association of Complement and Coagulation Pathway Proteins With Treatment Response in First-Episode Psychosis: A Longitudinal Analysis of the OPTiMiSE Clinical Trial.Schizophrenia bulletin · 2023Article
- Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.Clinical proteomics · 2023Article
- Article
- A Novel Blood Proteomic Signature for Prostate Cancer.Cancers · 2023Article
- Rationale, Design, and the Baseline Characteristics of the RHDGen (The Genetics of Rheumatic Heart Disease) Network Study†.Circulation. Genomic and precision medicine · 2023Article
- Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity.Nature communications · 2022Article
- Changes in the Proteome Profile of People Achieving Remission of Type 2 Diabetes after Bariatric Surgery.Journal of clinical medicine · 2021Article
- OptiMissP: A dashboard to assess missingness in proteomic data-independent acquisition mass spectrometry.PloS one · 2021Article
- Caspase-3 Cleaves Extracellular Vesicle Proteins During Auditory Brainstem Development.Frontiers in cellular neuroscience · 2020Article
- Insights Into the Proteomic Profiling of Extracellular Vesicles for the Identification of Early Biomarkers of Neurodegeneration.Frontiers in neurology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 2 institutions in 1 country.
Funding
Abstract
motivationData-independent acquisition mass spectrometry allows for comprehensive peptide detection and relative quantification than standard data-dependent approaches. While less prone to missing values, these still exist. Current approaches for handling the so-called missingness have challenges. We hypothesized that non-random missingness is a useful biological measure and demonstrate the importance of analysing missingness for proteomic discovery within a longitudinal study of disease activity.
resultsThe magnitude of missingness did not correlate with mean peptide concentration. The magnitude of missingness for each protein strongly correlated between collection time points (baseline, 3 months, 6 months; R = 0.95-0.97, confidence interval = 0.94-0.97) indicating little time-dependent effect. This allowed for the identification of proteins with outlier levels of missingness that differentiate between the patient groups characterized by different patterns of disease activity. The association of these proteins with disease activity was confirmed by machine learning techniques. Our novel approach complements analyses on complete observations and other missing value strategies in biomarker prediction of disease activity. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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.