Review



mouse microarray datasets  (Allen Institute for Brain Science)

 
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    Allen Institute for Brain Science mouse microarray datasets
    Mouse Microarray Datasets, supplied by Allen Institute for Brain Science, 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/mouse+crc+microarray+datasets/mouse+microarray+datasets/pm22864814-137-14-6
    Average 90 stars, based on 1 article reviews
    mouse microarray datasets - by Bioz Stars, 2026-10
    90/100 stars

    Images

    Related Articles

    Microarray:

    Article Title: Selection of novel reference genes for use in the human central nervous system: a BrainNet Europe Study.
    Article Snippet: The use of an appropriate reference gene to ensure accurate normalisation is crucial for the correct quantification of gene expression using qPCR assays and RNA arrays.. The main criterion for a gene to qualify as a reference gene is a stable expression across various cell types and experimental settings.. Several reference genes are commonly in use but more and more evidence reveals variations in their expression due to the presence of ongoing neuropathological disease processes, raising doubts concerning their use.



    Similar Products

    mouse crc microarray datasets  (Biotechnology Information)
    86
    Biotechnology Information mouse crc microarray datasets
    Differential expression analysis of <t>microarray</t> data from experimental and human colorectal cancer tissue. ( A , B ) Principal component analysis (PCA) plots of public microarray datasets from mouse GSE86299 ( A ) and human GSE8671 ( B ) tissue, comparing normal colon (blue) and colorectal cancer <t>(CRC)</t> (red). Mouse n = 8 per group; human n = 32 per group. These are representative datasets of a total of three analyzed . ( C , D ) Volcano plots displaying differential gene expression comparing murine ( C ) and human ( D ) CRC tissue with adjacent normal tissue. Genes down- and upregulated in cancer tissue are highlighted in blue and red, respectively. ( E ) Venn diagram illustrating the most common up- and downregulated genes across three experimental mouse models of colitis-associated colorectal cancer (CAC) derived from Gene Expression Omnibus (GEO) datasets. ( F ) Venn diagram illustrating the most common up- and downregulated genes across three human CRC datasets from GEO. The analysis was performed using the limma package version 3.16.2 with cut-offs of false discovery rate ( FDR ) < 0.05 (Benjamini–Hochberg method) and log 2 F C (fold change) < − 1 and > 1 .
    Mouse Crc Microarray Datasets, supplied by Biotechnology Information, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/mouse+crc+microarray+datasets/data+microarray/pmc12652218-88-14-23
    Average 86 stars, based on 1 article reviews
    mouse crc microarray datasets - by Bioz Stars, 2026-10
    86/100 stars
    		  Buy from Supplier

    Image Search Results


    Differential expression analysis of microarray data from experimental and human colorectal cancer tissue. ( A , B ) Principal component analysis (PCA) plots of public microarray datasets from mouse GSE86299 ( A ) and human GSE8671 ( B ) tissue, comparing normal colon (blue) and colorectal cancer (CRC) (red). Mouse n = 8 per group; human n = 32 per group. These are representative datasets of a total of three analyzed . ( C , D ) Volcano plots displaying differential gene expression comparing murine ( C ) and human ( D ) CRC tissue with adjacent normal tissue. Genes down- and upregulated in cancer tissue are highlighted in blue and red, respectively. ( E ) Venn diagram illustrating the most common up- and downregulated genes across three experimental mouse models of colitis-associated colorectal cancer (CAC) derived from Gene Expression Omnibus (GEO) datasets. ( F ) Venn diagram illustrating the most common up- and downregulated genes across three human CRC datasets from GEO. The analysis was performed using the limma package version 3.16.2 with cut-offs of false discovery rate ( FDR ) < 0.05 (Benjamini–Hochberg method) and log 2 F C (fold change) < − 1 and > 1 .

    Journal: International Journal of Molecular Sciences

    Article Title: Downregulation of Enteroendocrine Genes Predicts Survival in Colon Cancer: A Bioinformatics-Based Analysis

    doi: 10.3390/ijms262211127

    Figure Lengend Snippet: Differential expression analysis of microarray data from experimental and human colorectal cancer tissue. ( A , B ) Principal component analysis (PCA) plots of public microarray datasets from mouse GSE86299 ( A ) and human GSE8671 ( B ) tissue, comparing normal colon (blue) and colorectal cancer (CRC) (red). Mouse n = 8 per group; human n = 32 per group. These are representative datasets of a total of three analyzed . ( C , D ) Volcano plots displaying differential gene expression comparing murine ( C ) and human ( D ) CRC tissue with adjacent normal tissue. Genes down- and upregulated in cancer tissue are highlighted in blue and red, respectively. ( E ) Venn diagram illustrating the most common up- and downregulated genes across three experimental mouse models of colitis-associated colorectal cancer (CAC) derived from Gene Expression Omnibus (GEO) datasets. ( F ) Venn diagram illustrating the most common up- and downregulated genes across three human CRC datasets from GEO. The analysis was performed using the limma package version 3.16.2 with cut-offs of false discovery rate ( FDR ) < 0.05 (Benjamini–Hochberg method) and log 2 F C (fold change) < − 1 and > 1 .

    Article Snippet: We explored the presence or absence of secretory IEC markers by analyzing three different mouse CRC microarray datasets from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database ( GSE86299 , GSE31105 , and GSE64658 ).

    Techniques: Quantitative Proteomics, Microarray, Gene Expression, Derivative Assay