ArticleBioinformatics (Oxford, England)2012
Improving the TFold test for differential shotgun proteomics.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
What it found
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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.
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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.
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Who cites it
43 citing papers in PubMed, 83 citations in OpenAlex.
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- Proteomics reveals differentially regulated pathways when comparing grade 2 and 4 astrocytomas.PloS one · 2023Article
- Extracellular Vesicles fromToxins · 2022Article
- Simple, efficient and thorough shotgun proteomic analysis with PatternLab V.Nature protocols · 2022Review
- Genomic and proteomic analysis of Tausonia pullulans reveals a key role for a GH15 glucoamylase in starch hydrolysis.Applied microbiology and biotechnology · 2022Article
- Non-target molecular network and putative genes of flavonoid biosynthesis inFrontiers in plant science · 2022Article
- Dynamic Profile of S-Layer Proteins Controls Surface Properties of EmeticFrontiers in microbiology · 2022Article
- Skin-to-blood pH shift triggers metabolome and proteome global remodelling 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
3 authors at 2 institutions in 2 countries.
Funding
Abstract
unlabelledWe present an updated version of the TFold software for pinpointing differentially expressed proteins in shotgun proteomics experiments. Given an FDR bound, the updated approach uses a theoretical FDR estimator to maximize the number of identifications that satisfy both a fold-change cutoff that varies with the t-test P-value as a power law and a stringency criterion that aims to detect lowly abundant proteins. The new version has yielded significant improvements in sensitivity over the previous one. AVAILABILITY: Freely available for academic use at http://pcarvalho.com/patternlab.
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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.