CD Genomics uses bioinformatics to provide quantitative proteomics and help you explore the data information obtained by different protein quantification techniques. Our unique data analysis skills and the high-quality data analysis platform will exceed your expectations on your personalized data analysis.
Introduction of Quantitative Proteomics
Quantitative proteomics is the accurate identification and quantification of all proteins expressed in a genome or in a complex mixed system. It can be used to screen and find the differentially expressed proteins among samples caused by any factors, and to reveal the physiological and pathological functions of cells combined with bioinformatics. At the same time, some key proteins can be qualitatively and quantitatively analyzed.
Quantitative proteomics refers to the accurate quantitative analysis of the proteins of interest in a single genome sample or a complex mixed system based on protein full spectrum analysis. It can be used to compare the protein content in multiple samples, look for differentially expressed proteins and evaluate their functional characteristics. The input raw data can be obtained by iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) technology, TMT (Tandem Mass Tag) technology, Label-free (protein free-labeled quantification) technology, DIA (Data -independent acquisition) technology, Blood 580 technology and other protein quantification technologies. Relying on powerful information analysis and data processing capabilities, we provide users with efficient protein identification and quantitative analysis services.
Fig 1. Subnetwork diagram of the PARP-1-centered protein interaction map. (Jean-Philippe G, et al.2012)
Application Field
Quantitative proteomics can be used for but not limited to the following research:
Analysis of protein differential expression in multiple samples.
Study protein regulatory network.
Advantages of CD Genomics
Analyze proteomic data produced by different techniques.
An experienced analytical team.
Standardized analysis process.
Strict data quality control.
Reliable analysis results.
Fast analysis cycle.
CD Genomics Data Analysis Pipeline
Bioinformatic Analysis Content
Our quantitative proteomics service can analyze different type of input raw data with different analysis content. In addition, if you provide both transcriptome sequencing data and proteomics sequencing data, we can provide proteome and transcriptome association analysis. For more information, please contact us.
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Data quality assessment
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Statistical analysis of data
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Qualitative protein analysis
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Protein identification results
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Peptide length distribution
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Protein coverage distribution
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Protein function annotation
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Protein GO annotation
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Protein COG/KOG analysis
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Protein KEGG annotation
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Protein domain annotation
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Quantitative protein analysis
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Protein quantification results
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Repeatability analysis
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Protein differential analysis
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Odds ratio analysis
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Volcano map analysis
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Cluster analysis
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Analysis of GO enrichment of differential proteins
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COG/KOG analysis of differential proteins
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Pathway enrichment analysis of differential proteins
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Protein interaction networks analysis
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Association analysis with transcriptome
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Expression regulation analysis
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Correlation analysis of expression
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GO function enrichment association analysis
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GO function enrichment clustering heatmap
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KEGG pathway enrichment heat map
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For quantitative proteomics information analysis,if you have other needs, for example, based on proteomics sequencing data to detect mutations and new transcripts. We will provide appropriate biological information analysis content according to your needs, please feel free to contact us for details.
CD Genomics has successfully conducted quantitative proteomics data analysis on a variety of samples. Combined with rich project experience, strict data quality control and professional analysis process, to ensure that the project is carried out accurately and quickly. Please contact us for more information and a detailed quote.
Reference
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Jean-Philippe G, et al. Quantitative proteomics profiling of the poly(ADP-ribose)-related response to genotoxic stress. Nucleic Acids Research.2012 Sep;40(16):7788-805.
