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microarray gene expression transcriptome datasets  (Illumina Inc)


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    Illumina Inc microarray gene expression transcriptome datasets
    Three-step identification of HCC potential biomarkers. First, DEGs using non-fusion integrative method detected. Based on ComBat approach, the batch effect between data from two main <t>microarray</t> platforms (Affymetrix and Illumina), removed. Second, to deal with a more in-depth analysis of HCC expression datasets to identify potential diagnosis and prognosis biomarkers, classification methods and biomarker recognition conducted. Third, to evaluate the diagnostic performance in classifying HCC from normal, the risk score model was developed, and to assess the prognostic value of gene biomarkers, Kaplan–Meier (KM) survival analysis performed.
    Microarray Gene Expression Transcriptome Datasets, supplied by Illumina Inc, 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/result/microarray gene expression transcriptome datasets/product/Illumina Inc
    Average 90 stars, based on 1 article reviews
    microarray gene expression transcriptome datasets - by Bioz Stars, 2026-05
    90/100 stars

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    1) Product Images from "Detection of key mRNAs in liver tissue of hepatocellular carcinoma patients based on machine learning and bioinformatics analysis"

    Article Title: Detection of key mRNAs in liver tissue of hepatocellular carcinoma patients based on machine learning and bioinformatics analysis

    Journal: MethodsX

    doi: 10.1016/j.mex.2023.102021

    Three-step identification of HCC potential biomarkers. First, DEGs using non-fusion integrative method detected. Based on ComBat approach, the batch effect between data from two main microarray platforms (Affymetrix and Illumina), removed. Second, to deal with a more in-depth analysis of HCC expression datasets to identify potential diagnosis and prognosis biomarkers, classification methods and biomarker recognition conducted. Third, to evaluate the diagnostic performance in classifying HCC from normal, the risk score model was developed, and to assess the prognostic value of gene biomarkers, Kaplan–Meier (KM) survival analysis performed.
    Figure Legend Snippet: Three-step identification of HCC potential biomarkers. First, DEGs using non-fusion integrative method detected. Based on ComBat approach, the batch effect between data from two main microarray platforms (Affymetrix and Illumina), removed. Second, to deal with a more in-depth analysis of HCC expression datasets to identify potential diagnosis and prognosis biomarkers, classification methods and biomarker recognition conducted. Third, to evaluate the diagnostic performance in classifying HCC from normal, the risk score model was developed, and to assess the prognostic value of gene biomarkers, Kaplan–Meier (KM) survival analysis performed.

    Techniques Used: Microarray, Expressing, Biomarker Discovery, Diagnostic Assay



    Similar Products

    microarray gene expression transcriptome datasets  (Illumina Inc)
    90
    Illumina Inc microarray gene expression transcriptome datasets
    Three-step identification of HCC potential biomarkers. First, DEGs using non-fusion integrative method detected. Based on ComBat approach, the batch effect between data from two main <t>microarray</t> platforms (Affymetrix and Illumina), removed. Second, to deal with a more in-depth analysis of HCC expression datasets to identify potential diagnosis and prognosis biomarkers, classification methods and biomarker recognition conducted. Third, to evaluate the diagnostic performance in classifying HCC from normal, the risk score model was developed, and to assess the prognostic value of gene biomarkers, Kaplan–Meier (KM) survival analysis performed.
    Microarray Gene Expression Transcriptome Datasets, supplied by Illumina Inc, 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/result/microarray gene expression transcriptome datasets/product/Illumina Inc
    Average 90 stars, based on 1 article reviews
    microarray gene expression transcriptome datasets - by Bioz Stars, 2026-05
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Three-step identification of HCC potential biomarkers. First, DEGs using non-fusion integrative method detected. Based on ComBat approach, the batch effect between data from two main microarray platforms (Affymetrix and Illumina), removed. Second, to deal with a more in-depth analysis of HCC expression datasets to identify potential diagnosis and prognosis biomarkers, classification methods and biomarker recognition conducted. Third, to evaluate the diagnostic performance in classifying HCC from normal, the risk score model was developed, and to assess the prognostic value of gene biomarkers, Kaplan–Meier (KM) survival analysis performed.

    Journal: MethodsX

    Article Title: Detection of key mRNAs in liver tissue of hepatocellular carcinoma patients based on machine learning and bioinformatics analysis

    doi: 10.1016/j.mex.2023.102021

    Figure Lengend Snippet: Three-step identification of HCC potential biomarkers. First, DEGs using non-fusion integrative method detected. Based on ComBat approach, the batch effect between data from two main microarray platforms (Affymetrix and Illumina), removed. Second, to deal with a more in-depth analysis of HCC expression datasets to identify potential diagnosis and prognosis biomarkers, classification methods and biomarker recognition conducted. Third, to evaluate the diagnostic performance in classifying HCC from normal, the risk score model was developed, and to assess the prognostic value of gene biomarkers, Kaplan–Meier (KM) survival analysis performed.

    Article Snippet: In this investigation, which was based on the Illumina and Affymetrix platforms, seven microarray gene expression transcriptome datasets were considered.

    Techniques: Microarray, Expressing, Biomarker Discovery, Diagnostic Assay