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maxquant perseus proteomics analysis software  (Perseus Proteomics)

 
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    Perseus Proteomics maxquant perseus proteomics analysis software
    Shotgun <t>proteomics</t> 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.
    Maxquant Perseus Proteomics Analysis Software, supplied by Perseus Proteomics, 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/perseus+proteomics+software/pmc08925122-78-15-17
    Average 90 stars, based on 1 article reviews
    maxquant perseus proteomics analysis software - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Salivary Proteomics Identifies Transthyretin as a Biomarker of Early Dementia Conversion"

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

    Journal: Journal of Alzheimer's Disease Reports

    doi: 10.3233/ADR-210056

    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.
    Figure Legend 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.

    Techniques Used: Functional Assay, Quantitative Proteomics, Expressing

    Related Articles

    other:

    Article Title: Nfkb2 deficiency and its impact on plasma cells and immunoglobulin expression in murine small intestinal mucosa
    Article Snippet: Protein groups with significant intensity regulation were determined according to Welch’s T test using the Perseus proteomics data analysis tool ( ).

    Article Title: Physioxia rewires mitochondrial complex composition to protect stem cell viability
    Article Snippet: In addition, data from proteomic analysis were loaded to Perseus proteomics software for further statistical analysis ( ) [ ].

    Article Title: An insight in proteome profiling of Tuta absoluta larvae after entomopathogenic fungal infection.
    Article Snippet: Perseus proteomics software version 1.6.2.2 (https://www.perseus-framework.org) was used for statistical analysis, where p values were calculated by Students t test.

    Article Title: Integrated Proteomics Unveils Nuclear PDE3A2 as a Regulator of Cardiac Myocyte Hypertrophy
    Article Snippet: Statistical significance tests for proteomics data were performed within the Perseus proteomics software package (v1.6.1.1).

    Article Title: Infection of Endothelial Cells with Acinetobacter baumannii Reveals Remodelling of Mitochondrial Protein Complexes
    Article Snippet: Data were loaded to Perseus proteomics software ( ) and gene ontology terms for cellular components were added to each protein.

    Article Title: Physioxia rewires mitochondrial complex composition to protect stem cell viability
    Article Snippet: In addition, data from proteomic analysis were loaded to Perseus proteomics software for further statistical analysis (Table S1)21.

    Article Title: Infection of Endothelial Cells with Acinetobacter baumannii Reveals Remodelling of Mitochondrial Protein Complexes.
    Article Snippet: Data were loaded to Perseus proteomics software (58) and gene ontology terms for cellular components were added to each protein.



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    Shotgun <t>proteomics</t> 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.
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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

    Journal: The EMBO Journal

    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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