2021
DOI: 10.1016/j.mcpro.2021.100052
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New Proteomic Signatures to Distinguish Between Zika and Dengue Infections

Abstract: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, a… Show more

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Cited by 11 publications
(17 citation statements)
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“…Data and analysis: We obtained the RAW files from Allgoewer et al (2021). The data had been collected in data-independent acquisition mode, comprising 124 patient and 20 quality control samples.…”
Section: Methodsmentioning
confidence: 99%
See 3 more Smart Citations
“…Data and analysis: We obtained the RAW files from Allgoewer et al (2021). The data had been collected in data-independent acquisition mode, comprising 124 patient and 20 quality control samples.…”
Section: Methodsmentioning
confidence: 99%
“…We prepared spectral libraries based on data acquired in data-dependent acquisition mode from pooled and fractionated serum samples of Zika and dengue patients (Allgoewer et al 2021) using the Pulsar search engine within Spectronaut 14. Settings included Trypsin/P digest, peptide length of 7 to 52 amino acids and up to two missed cleavages.…”
Section: Methodsmentioning
confidence: 99%
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“…The majority of clinical proteomics studies to date have focussed on DENV disease progression. More recently unique protein signatures in patient serum were identified that could distinguish between ZIKV and DENV infection[ 225 ]. Thirteen differentially expressed proteins were identified, with 10 upregulated in ZIKV compared to DENV infection.…”
Section: Mass Spectrometry-based Approaches To Study Flavivirus Infection Biologymentioning
confidence: 99%