ArticleNature communications2024
Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
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Who cites it
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reproducibility Crossroads: Impact of Statistical Choices on Proteomics Functional Enrichment.International journal of molecular sciences · 2025Pooled it
- Differential protein expression analysis of quantitative mass spectrometry data using DEqMS.Nature protocols · 2026Review
- Adjunctive nebulization of Idursulfase to intravenous treatment enhances cardiac proteome adaptations in IDS-KO mice.bioRxiv : the preprint server for biology · 2026Article
- TRPA1 deficiency alters brown adipose tissue proteome and thermogenic gene expression during cold exposure in mice.Biochemistry and biophysics reports · 2026Article
- Potential of SERS and proteomics for biomarker detection in cancer cells.Analytical and bioanalytical chemistry · 2026Article
- Multi-metric evaluation and parametric optimization of stochastic gradient boosting machines for genomic prediction and selection in wheat (Triticum aestivum) breeding.G3 (Bethesda, Md.) · 2026Article
- The Bunyamwera orthobunyavirus Gc glycoprotein head and stalk drives an infectious virion assembly pathway specific for the insect host.PLoS pathogens · 2026Article
- MLMarker: a machine learning framework for tissue inference and biomarker discovery.Genome biology · 2026Article
- Profiling of extracellular vesicles from primary hepatocytes, organoids, and mash patients identifies cell injury-specific signatures.Scientific reports · 2026Article
- Spinal cord extracellular matrix hydrogel enhances organoid maturation and functional regeneration after spinal cord injury.Materials today. Bio · 2026Article
- Clarifying the scope and capabilities of ROTS in differential expression analysis.Bioinformatics (Oxford, England) · 2026Article
- An Adnp frameshift variant disrupts Wnt signalling inducing chromatocytoskeletal defects and autism-related behaviour in male mice.EBioMedicine · 2026Article
- Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- JUMPlion improves quantitative DIA proteomics through ion-level recovery of missing values.bioRxiv : the preprint server for biology · 2026Article
- DeeDeeExperiment: building an infrastructure for integrating and managing omics data analysis results in R/Bioconductor.Bioinformatics (Oxford, England) · 2026Article
- Computational proteomics to enhance personalized treatment of COVID-19 and Long COVID.Clinical proteomics · 2026Review
- Spectronaut and DIA-NN: A Comparison of their Performance in the Analysis of Lung Adenocarcinoma Biopsies.ACS omega · 2026Article
- Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.Journal of medicinal chemistry · 2026Review
- Illustration of the gut-immune-liver axis in early-stage alcohol-related liver disease: role and non-invasive potentiation of biomarkers and peptidomic signatures.Npj gut and liver · 2026Article
- Proteomics of long-term acclimation of the desert cyanobacteriumCurrent research in microbial sciences · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Identification of differentially expressed proteins in a proteomics workflow typically encompasses five key steps: raw data quantification, expression matrix construction, matrix normalization, missing value imputation (MVI), and differential expression analysis. The plethora of options in each step makes it challenging to identify optimal workflows that maximize the identification of differentially expressed proteins. To identify optimal workflows and their common properties, we conduct an extensive study involving 34,576 combinatoric experiments on 24 gold standard spike-in datasets. Applying frequent pattern mining techniques to top-ranked workflows, we uncover high-performing rules that demonstrate optimality has conserved properties. Via machine learning, we confirm optimal workflows are indeed predictable, with average cross-validation F1 scores and Matthew's correlation coefficients surpassing 0.84. We introduce an ensemble inference to integrate results from individual top-performing workflows for expanding differential proteome coverage and resolve inconsistencies. Ensemble inference provides gains in pAUC (up to 4.61%) and G-mean (up to 11.14%) and facilitates effective aggregation of information across varied quantification approaches such as topN, directLFQ, MaxLFQ intensities, and spectral counts. However, further development and evaluation are needed to establish acceptable frameworks for conducting ensemble inference on multiple proteomics workflows.
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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.