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low temperature-treated whole-genome microarray data set  (Kenshin Trading)

 
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    Kenshin Trading low temperature-treated whole-genome microarray data set
    <t>Microarray</t> expression represented as heat map and hierarchical clustering of 36 TIFY genes against different low temperatures such as control (C1 and K1), 4°C (C2 and K2), 0°C (C3 and K3), −2°C (C4 and K4), and −4°C (C5 and K5) in B. rapa . Here, “C” and “K” stand for “Chiifu” and “Kenshin” two inbred lines of B. rapa , respectively. Expression clusters are shown in the left (Cl1–Cl5) and gene name against each expression has mentioned at right side. Color bars with values at the base represent differential expression in microarray.
    Low Temperature Treated Whole Genome Microarray Data Set, supplied by Kenshin Trading, 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/microarray+data+set/pmc04923152-63-4-27?v=Kenshin+Trading
    Average 90 stars, based on 1 article reviews
    low temperature-treated whole-genome microarray data set - by Bioz Stars, 2026-08
    90/100 stars

    Images

    1) Product Images from "A Genome-Wide Analysis Reveals Stress and Hormone Responsive Patterns of TIFY Family Genes in Brassica rapa"

    Article Title: A Genome-Wide Analysis Reveals Stress and Hormone Responsive Patterns of TIFY Family Genes in Brassica rapa

    Journal: Frontiers in Plant Science

    doi: 10.3389/fpls.2016.00936

    Microarray expression represented as heat map and hierarchical clustering of 36 TIFY genes against different low temperatures such as control (C1 and K1), 4°C (C2 and K2), 0°C (C3 and K3), −2°C (C4 and K4), and −4°C (C5 and K5) in B. rapa . Here, “C” and “K” stand for “Chiifu” and “Kenshin” two inbred lines of B. rapa , respectively. Expression clusters are shown in the left (Cl1–Cl5) and gene name against each expression has mentioned at right side. Color bars with values at the base represent differential expression in microarray.
    Figure Legend Snippet: Microarray expression represented as heat map and hierarchical clustering of 36 TIFY genes against different low temperatures such as control (C1 and K1), 4°C (C2 and K2), 0°C (C3 and K3), −2°C (C4 and K4), and −4°C (C5 and K5) in B. rapa . Here, “C” and “K” stand for “Chiifu” and “Kenshin” two inbred lines of B. rapa , respectively. Expression clusters are shown in the left (Cl1–Cl5) and gene name against each expression has mentioned at right side. Color bars with values at the base represent differential expression in microarray.

    Techniques Used: Microarray, Expressing, Control, Quantitative Proteomics



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    Image Search Results


    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

    Normalization of expression data is performed using RMA and DESeq2 algorithms on Affymetrix microarray (Set2) and RNA sequencing (Set3, Set4, and Set5) datasets respectively. BTK subtypes are generated using the same consensus clustering methodology in other four cohorts. BTK subtypes in each of these cohorts are significantly associated ( p < 0.05) with BTK mRNA Expression ( A -Set2, B -Set3, C -Set4 and D -Set5).

    Journal: Blood Cancer Journal

    Article Title: Transcriptomic clustering of chronic lymphocytic leukemia: molecular subtypes based on Bruton’s tyrosine kinase expression levels

    doi: 10.1038/s41408-024-01196-3

    Figure Lengend Snippet: Normalization of expression data is performed using RMA and DESeq2 algorithms on Affymetrix microarray (Set2) and RNA sequencing (Set3, Set4, and Set5) datasets respectively. BTK subtypes are generated using the same consensus clustering methodology in other four cohorts. BTK subtypes in each of these cohorts are significantly associated ( p < 0.05) with BTK mRNA Expression ( A -Set2, B -Set3, C -Set4 and D -Set5).

    Article Snippet: Initial clustering and assessment of association with BTK mRNA expression was performed using Affymetrix Microarray data set that has 130 patients [ ] designated as Set1.

    Techniques: Expressing, Microarray, RNA Sequencing Assay, Generated