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maxquant proteomics analysis thermo .raw  (Thermo Fisher)


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    Thermo Fisher maxquant proteomics analysis thermo .raw
    Maxquant Proteomics Analysis Thermo .Raw, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/maxquant+analysis/maxquant+proteomics+analysis+thermo++raw/pmc07191556-926-41-40
    Average 90 stars, based on 1 article reviews
    maxquant proteomics analysis thermo .raw - by Bioz Stars, 2026-10
    90/100 stars

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    Data-dependent acquisition:

    Article Title: Methyl-Metabolite Depletion Elicits Adaptive Responses to Support Heterochromatin Stability and Epigenetic Persistence
    Article Snippet: .. DDA settings were as follows: window size = 2.0 m/z, resolution = 17,500, automatic gain control target = 2 × 10 5 , DDA maximum fill time = 150 ms, and normalized collision energy = 28. . MaxQuant Proteomics Analysis Thermo .raw DDA files were analyzed using MaxQuant v1.6.2.6 ( Cox et al., 2014 ) using the default settings with the following exceptions: Labels: 1, Arg10; Instrument: Orbitrap; LFQ: LFQ min. ratio count: 2, LFQ min. number of neighbors: 3, LFQ average number of neighbors: 6; FASTQ File: Proteome: H. Sapiens Proteome ID UP000005640. ..

    Control:

    Article Title: Methyl-Metabolite Depletion Elicits Adaptive Responses to Support Heterochromatin Stability and Epigenetic Persistence
    Article Snippet: .. DDA settings were as follows: window size = 2.0 m/z, resolution = 17,500, automatic gain control target = 2 × 10 5 , DDA maximum fill time = 150 ms, and normalized collision energy = 28. . MaxQuant Proteomics Analysis Thermo .raw DDA files were analyzed using MaxQuant v1.6.2.6 ( Cox et al., 2014 ) using the default settings with the following exceptions: Labels: 1, Arg10; Instrument: Orbitrap; LFQ: LFQ min. ratio count: 2, LFQ min. number of neighbors: 3, LFQ average number of neighbors: 6; FASTQ File: Proteome: H. Sapiens Proteome ID UP000005640. ..



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    Image Search Results


    Shotgun proteomics to compare saliva and CSF and correlation analysis of differentially expressed genes in saliva. A) GO Biological pathways for salivary proteins. B) Number of shared proteins between saliva and CSF. C) Number of shared hits between common proteins and AD related proteins. D) STRING map shows the functional association based on the string database indicating the interactome of commonly shared proteins in saliva and CSF with AD. E) Volcano plots showing differential expression in saliva and F) CSF between AD and CN. G) Abundance rank dot plots for saliva and H) CSF shows the range of expression levels for the differentially expressed proteins. I) STRING map shows the interaction of differentially expressed proteins in saliva and J) in CSF. In the STRING map, the pink line represents the known interaction that is experimentally determined, blue line represents the known interaction from curated databases, green line represents predicted interaction due to gene neighborhood, red line represents prediction due to gene fusions and dark blue line represents prediction due to gene co-occurrence.

    Journal: Journal of Alzheimer's Disease Reports

    Article Title: Salivary Proteomics Identifies Transthyretin as a Biomarker of Early Dementia Conversion

    doi: 10.3233/ADR-210056

    Figure Lengend Snippet: Shotgun proteomics to compare saliva and CSF and correlation analysis of differentially expressed genes in saliva. A) GO Biological pathways for salivary proteins. B) Number of shared proteins between saliva and CSF. C) Number of shared hits between common proteins and AD related proteins. D) STRING map shows the functional association based on the string database indicating the interactome of commonly shared proteins in saliva and CSF with AD. E) Volcano plots showing differential expression in saliva and F) CSF between AD and CN. G) Abundance rank dot plots for saliva and H) CSF shows the range of expression levels for the differentially expressed proteins. I) STRING map shows the interaction of differentially expressed proteins in saliva and J) in CSF. In the STRING map, the pink line represents the known interaction that is experimentally determined, blue line represents the known interaction from curated databases, green line represents predicted interaction due to gene neighborhood, red line represents prediction due to gene fusions and dark blue line represents prediction due to gene co-occurrence.

    Article Snippet: CSF and saliva proteome from AD patients and age-matched control subjects were investigated using the open-source MaxQuant Perseus proteomics analysis software; protein expression variability within the clinical group was analyzed using homogeneity of variance.

    Techniques: Functional Assay, Quantitative Proteomics, Expressing

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    Article Title: An optimized quantitative proteomics method establishes the cell type‐resolved mouse brain secretome

    doi: 10.15252/embj.2020105693

    Figure Lengend Snippet:

    Article Snippet: The results of the MaxQuant analysis were used to generate DIA spectral libraries of proteins in Spectronaut Pulsar X (Biognosys).

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