ReviewNature protocols2022
Simple, efficient and thorough shotgun proteomic analysis with PatternLab V.
Review in Nature protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 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
46 citing papers in PubMed.
- Differential protein expression analysis of quantitative mass spectrometry data using DEqMS.Nature protocols · 2026Review
- Article
- Cellular and molecular responses ofMicrobiology spectrum · 2026Article
- Cancer Genes: Origins and Directions.Viruses · 2026Review
- Fungal Extracellular Vesicles are Recoverable Across Variable Ultracentrifugation Speeds but Display Species-specific Profiles of Sedimentation.The Journal of membrane biology · 2026Article
- Quinoa bioester application shifts human skin proteome toward molecular profiles associated with younger age.Communications biology · 2026Observational
- Chiral methionine oxidation reagents reveal stereospecific proteome modifications.bioRxiv : the preprint server for biology · 2026Article
- Effects of human immunoglobulins onmBio · 2026Article
- Human milk oligosaccharides promote synaptogenesis and neurite outgrowth in human cortical organoids.Biochemistry and biophysics reports · 2026Article
- Proteomic dataset of MECP2-deficient and wild-type human brain organoids under spaceflight and ground conditions.Scientific data · 2026Article
- Spectral Cruncher: A Visualization Tool Integrating Manual Curation, Ion-Intensity Prediction, and De Novo Tag Generation.Journal of the American Society for Mass Spectrometry · 2026Article
- Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.Journal of medicinal chemistry · 2026Review
- Pathogenic diversity ofCell surface (Amsterdam, Netherlands) · 2025Article
- An anti-adhesive peptide found in extracellular vesicles fromCell surface (Amsterdam, Netherlands) · 2025Article
- From Isolation to Genomics: Characterization ofJournal of fungi (Basel, Switzerland) · 2025Article
- Cardioprotective effects of extracellular vesicles from hypoxia-preconditioned mesenchymal stromal cells in experimental pulmonary arterial hypertension.Stem cell research & therapy · 2025Article
- The flippases Apt1 and Apt2 differentially influence extracellular vesicle cargo and polysaccharide secretion in Cryptococcus neoformans.Journal of proteomics · 2025Article
- Article
- Comparative Gut Proteome ofMicroorganisms · 2025Article
- Enhancing photosynthesis under salt stress via directed evolution in cyanobacteria.Plant physiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
Abstract
Shotgun proteomics aims to identify and quantify the thousands of proteins in complex mixtures such as cell and tissue lysates and biological fluids. This approach uses liquid chromatography coupled with tandem mass spectrometry and typically generates hundreds of thousands of mass spectra that require specialized computational environments for data analysis. PatternLab for proteomics is a unified computational environment for analyzing shotgun proteomic data. PatternLab V (PLV) is the most comprehensive and crucial update so far, the result of intensive interaction with the proteomics community over several years. All PLV modules have been optimized and its graphical user interface has been completely updated for improved user experience. Major improvements were made to all aspects of the software, ranging from boosting the number of protein identifications to faster extraction of ion chromatograms. PLV provides modules for preparing sequence databases, protein identification, statistical filtering and in-depth result browsing for both labeled and label-free quantitation. The PepExplorer module can even pinpoint de novo sequenced peptides not already present in the database. PLV is of broad applicability and therefore suitable for challenging experimental setups, such as time-course experiments and data handling from unsequenced organisms. PLV interfaces with widely adopted software and community initiatives, e.g., Comet, Skyline, PEAKS and PRIDE. It is freely available at http://www.patternlabforproteomics.org .
Indexed as
Identifiers
35411045What 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.