ArticleBioinformatics (Oxford, England)2014
Pipasic: similarity and expression correction for strain-level identification and quantification in metaproteomics.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- MARLOWE: taxonomic characterization of unknown samples for forensics using de novo peptide identification.Scientific reports · 2026Article
- From Identification to Insight: Making Full Use of the Diagnostic Potential of MS/MS Proteotyping in Clinical Microbiology Using Efficient Bioinformatics.Journal of proteome research · 2025Review
- MultiStageSearch: An Iterative Workflow for Unbiased Taxonomic Analysis of Pathogens Using Proteogenomics.Journal of proteome research · 2025Article
- Moving Toward Metaproteogenomics: A Computational Perspective on Analyzing Microbial Samples via Proteogenomics.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Bioinformatic Workflows for Metaproteomics.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Pairing metagenomics and metaproteomics to characterize ecological niches and metabolic essentiality of gut microbiomes.ISME communications · 2024Article
- PepGM: a probabilistic graphical model for taxonomic inference of viral proteome samples with associated confidence scores.Bioinformatics (Oxford, England) · 2023Article
- Evaluation of the Limit of Detection of Bacteria by Tandem Mass Spectrometry Proteotyping and Phylopeptidomics.Microorganisms · 2023Article
- An adaptive direction-assisted test for microbiome compositional data.Bioinformatics (Oxford, England) · 2022Article
- Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach.Journal of the American Society for Mass Spectrometry · 2022Article
- Deep learning for peptide identification from metaproteomics datasets.Journal of proteomics · 2021Article
- Robust Accurate Identification and Biomass Estimates of Microorganisms via Tandem Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2020Article
- Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2018Article
- MPA Portable: A Stand-Alone Software Package for Analyzing Metaproteome Samples on the Go.Analytical chemistry · 2018Article
- Metaproteomic analysis of human gut microbiota: where are we heading?Journal of biomedical science · 2017Review
- Typing and Characterization of Bacteria Using Bottom-up Tandem Mass Spectrometry Proteomics.Molecular & cellular proteomics : MCP · 2017Article
- High-resolution characterization of the human microbiome.Translational research : the journal of laboratory and clinical medicine · 2017Review
- Article
- Systems-based approaches to unravel multi-species microbial community functioning.Computational and structural biotechnology journal · 2015Review
- Proteogenomics: concepts, applications and computational strategies.Nature methods · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationMetaproteomic analysis allows studying the interplay of organisms or functional groups and has become increasingly popular also for diagnostic purposes. However, difficulties arise owing to the high sequence similarity between related organisms. Further, the state of conservation of proteins between species can be correlated with their expression level, which can lead to significant bias in results and interpretation. These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions.
resultsWe introduce Pipasic (peptide intensity-weighted proteome abundance similarity correction) as a tool that corrects identification and spectral counting-based quantification results using peptide similarity estimation and expression level weighting within a non-negative lasso framework. Pipasic has distinct advantages over approaches only regarding unique peptides or aggregating results to the lowest common ancestor, as demonstrated on examples of viral diagnostics and an acid mine drainage dataset. AVAILABILITY AND IMPLEMENTATION: Pipasic source code is freely available from https://sourceforge.net/projects/pipasic/. CONTACT: RenardB@rki.de 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.