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microarray data set gse65194  (Biotechnology Information)
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Biotechnology Information microarray data set gse65194
Verification of expression level of hub genes and survival analysis of up-regulated genes. Part (A) represents the survival graph of each hub gene. Line color in black represents the survival of the patient when the expression of the genes is low; red line below represents the probability of the survival of the patient when genes with high expression. Part (B) represents the box plot of 2 hub genes constructed using TCGA and GTEx expression data. Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Different color code boxes represent the breast cancer tissue group, gray was the normal tissue group, and asterisk represented P < .01. The dots represented expression in each sample. Part (C) of figure represents the validity expression of 8 hub genes using test and control samples of <t>GSE65194</t> data set. Different color code boxes represent the TNBC samples, and gray represents the normal sample. The dots represented expression in each sample.
Microarray Data Set Gse65194, supplied by Biotechnology Information, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Verification of expression level of hub genes and survival analysis of up-regulated genes. Part (A) represents the survival graph of each hub gene. Line color in black represents the survival of the patient when the expression of the genes is low; red line below represents the probability of the survival of the patient when genes with high expression. Part (B) represents the box plot of 2 hub genes constructed using TCGA and GTEx expression data. Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Different color code boxes represent the breast cancer tissue group, gray was the normal tissue group, and asterisk represented P < .01. The dots represented expression in each sample. Part (C) of figure represents the validity expression of 8 hub genes using test and control samples of GSE65194 data set. Different color code boxes represent the TNBC samples, and gray represents the normal sample. The dots represented expression in each sample.

Journal: Bioinformatics and Biology Insights

Article Title: Bioinformatics-Driven Investigations of Signature Biomarkers for Triple-Negative Breast Cancer

doi: 10.1177/11779322241271565

Figure Lengend Snippet: Verification of expression level of hub genes and survival analysis of up-regulated genes. Part (A) represents the survival graph of each hub gene. Line color in black represents the survival of the patient when the expression of the genes is low; red line below represents the probability of the survival of the patient when genes with high expression. Part (B) represents the box plot of 2 hub genes constructed using TCGA and GTEx expression data. Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Different color code boxes represent the breast cancer tissue group, gray was the normal tissue group, and asterisk represented P < .01. The dots represented expression in each sample. Part (C) of figure represents the validity expression of 8 hub genes using test and control samples of GSE65194 data set. Different color code boxes represent the TNBC samples, and gray represents the normal sample. The dots represented expression in each sample.

Article Snippet: Microarray data set GSE65194 from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus was used for identification of differentially expressed genes (DEGs) using R software.

Techniques: Expressing, Construct, Gene Expression, Control

Verification of expression level of hub genes and survival analysis of down-regulated genes. In Part (A), each case represents the survival graph of each hub gene. Line color in black represents the survival of the patient when the expression of the genes is high; red line below represents the probability of the survival of the patient when genes with low expression. Part (B) represents the box plot of 2 hub genes constructed using TCGA and GTEx expression data. Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Different color code boxes represent the breast cancer tissue group, gray was the normal tissue group, and asterisk represented P < .01. The dots represented expression in each sample. Part (C) of figure represents the validity expression of 8 hub genes using test and control samples of “GSE65194” data set. Different color code boxes represent the TNBC samples, and gray represents the normal sample. The dots represented expression in each sample.

Journal: Bioinformatics and Biology Insights

Article Title: Bioinformatics-Driven Investigations of Signature Biomarkers for Triple-Negative Breast Cancer

doi: 10.1177/11779322241271565

Figure Lengend Snippet: Verification of expression level of hub genes and survival analysis of down-regulated genes. In Part (A), each case represents the survival graph of each hub gene. Line color in black represents the survival of the patient when the expression of the genes is high; red line below represents the probability of the survival of the patient when genes with low expression. Part (B) represents the box plot of 2 hub genes constructed using TCGA and GTEx expression data. Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Different color code boxes represent the breast cancer tissue group, gray was the normal tissue group, and asterisk represented P < .01. The dots represented expression in each sample. Part (C) of figure represents the validity expression of 8 hub genes using test and control samples of “GSE65194” data set. Different color code boxes represent the TNBC samples, and gray represents the normal sample. The dots represented expression in each sample.

Article Snippet: Microarray data set GSE65194 from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus was used for identification of differentially expressed genes (DEGs) using R software.

Techniques: Expressing, Construct, Gene Expression, Control