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raw microarray data (.cel files  (Thermo Fisher)


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    Structured Review

    Thermo Fisher raw microarray data (.cel files
    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent <t>microarray</t> experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.
    Raw Microarray Data (.Cel Files, supplied by Thermo Fisher, 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+cel+data+files/pmc02045681-248-2-5
    Average 90 stars, based on 1 article reviews
    raw microarray data (.cel files - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Genomic expression during human myelopoiesis"

    Article Title: Genomic expression during human myelopoiesis

    Journal: BMC Genomics

    doi: 10.1186/1471-2164-8-264

    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent microarray experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.
    Figure Legend Snippet: Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent microarray experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.

    Techniques Used: Expressing, Microarray

    Related Articles

    Microarray:

    Article Title: Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes
    Article Snippet: .. Affymetrix microarray raw data (.CEL files) were downloaded from GEO using the accession IDs provided in . ..

    Article Title: Statistical Methods for Meta-Analysis of Microarray Data: A Comparative Study
    Article Snippet: Systematic integration of microarrays from different sources increases statistical power of detecting differentially expressed genes and allows assessment of heterogeneity.. The challenge, however, is in designing and implementing efficient analytic methodologies for combining data generated by different research groups and platforms.. The widely used strategy mainly focuses on integrating preprocessed data without having access to the original raw data that yielded the initial results.

    Article Title: Data Integration in Genetics and Genomics: Methods and Challenges
    Article Snippet: .. In a recent study, our group proposed a quality measure based on the detection P -values estimated from Affymetrix microarray raw data [ , ]. .. Using an effect-size model, we demonstrated that the incorporation of quality weights into the study-specific test statistics, within a meta-analysis of two Affymetrix microarray studies, produced more biologically meaningful results than the unweighted analysis.

    Article Title: Genomic expression during human myelopoiesis
    Article Snippet: .. In particular, raw microarray data (Affymetrix .CEL files) were obtained for a total of 24 samples from 8 different cell types of all myelopoietic lineages, representing a reference dataset for a comprehensive analysis of genomic expression during cell differentiation. ..

    Article Title: microCLIP super learning framework uncovers functional transcriptome-wide miRNA interactions
    Article Snippet: .. In-house analysis was initiated from microarray raw data (Affymetrix.CEL files). ..

    other:

    Article Title: An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR -mutant tumors
    Article Snippet: Raw expression microarray data (Affymetrix CEL files) 3.

    Article Title: Identification of common key genes and pathways between type 1 diabetes and multiple sclerosis using transcriptome and interactome analysis.
    Article Snippet: Purpose Type 1 diabetes (T1D) and multiple sclerosis (MS) are classified as T cell-mediated autoimmune diseases.. Although convergent evidence proposed common genetic architecture for autoimmune diseases, it remains a challenge to identify them.. This study aimed to determine common gene signature and pathways in T1D and MS via systems biology approach.

    Article Title: Elevated S100A8/S100A9 expression causes glucocorticoid resistance in MLL-rearranged infant acute lymphoblastic leukemia.
    Article Snippet: For the analysis of differentially expressed genes between prednisolone sensitive and resistant patients, raw microarray data (Affymetrix HU133plus2.0 GeneChips) were collectively normalized using variance-stabilizing normalization (VSN),22 and differential gene expression was statistically evaluated using linear models for microarray analyses.23,24 A detailed description of the processing of RNA samples and the generation of the gene expression profiles are previously described elsewhere.11 Gene-set enrichment analysis25 was used to evaluate enrichment of genes encoding S100 protein family members in prednisolone-resistant MLL-rearranged infant ALL samples.

    Expressing:

    Article Title: Genomic expression during human myelopoiesis
    Article Snippet: .. In particular, raw microarray data (Affymetrix .CEL files) were obtained for a total of 24 samples from 8 different cell types of all myelopoietic lineages, representing a reference dataset for a comprehensive analysis of genomic expression during cell differentiation. ..

    Cell Differentiation:

    Article Title: Genomic expression during human myelopoiesis
    Article Snippet: .. In particular, raw microarray data (Affymetrix .CEL files) were obtained for a total of 24 samples from 8 different cell types of all myelopoietic lineages, representing a reference dataset for a comprehensive analysis of genomic expression during cell differentiation. ..



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    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent <t>microarray</t> experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.
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    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent <t>microarray</t> experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.
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    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent <t>microarray</t> experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.
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    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent <t>microarray</t> experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.
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    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent <t>microarray</t> experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.
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    Image Search Results


    Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent microarray experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.

    Journal: BMC Genomics

    Article Title: Genomic expression during human myelopoiesis

    doi: 10.1186/1471-2164-8-264

    Figure Lengend Snippet: Gene expression dataset . A) The gene expression dataset analyzed comprises cell samples from different levels of myeloid differentiation process (stem/progenitor cells, precursors and terminally differentiated cells). The graph describes relationships between the cellular contexts analyzed within myeloid differentiation tree. For each cell type, the number of samples examined with independent microarray experiments is indicated in brackets. B) Dendrogram obtained by unsupervised hierarchical clustering on gene expression data matrix. Pearson correlation and average were used as similarity measure and linking method, respectively.

    Article Snippet: In particular, raw microarray data (Affymetrix .CEL files) were obtained for a total of 24 samples from 8 different cell types of all myelopoietic lineages, representing a reference dataset for a comprehensive analysis of genomic expression during cell differentiation.

    Techniques: Expressing, Microarray