BioSignatureGX™ Gene Expression Analysis

BioSignatureGX™ Gene Expression Analysis offers a model-based analysis of microarray data including classical statistical analyses with multiple normalization techniques. Because BioSignatureGX™ incorporates Bayesian network learning and modeling for its analysis of gene groups and single genes, sensitivity of dectecting more subtle modulations in genes is possible.

Unlike typical bioinformatics analysis, BioSignatureGX™ Gene Expression Analysis allows you to compare data from multiple conditions and various time points, as well as accounting for different genotypes, gender, and species/race. Additionally, any new gene expression analysis data is easily incorporated into existing data sets enabling comparisons of new genotypes, experimental environments or developmental states.

BioSignatureGX™ Gene Expression Analysis of microarray data will maximize the value of large, complex datasets. BioSignatureGX™ Analysis includes:



    Classic statistical analysis - normalization schemes (global scaling, mean-, median-, lowness-normalization and percentile rank, z-score, Bayesian t-test, ANOVA) 
    Efficient management of complex time-course data 
    Identification and prioritization of target genes  
    Comprehensive pathway analysis 
    Comprehensive Gene Ontology (GO) analysis using over 3000 GO biological process categories 
    Identification of mechanistic genes underlying genetic relationships  
    CpG island chromosomes mapping of all significant mechanistic genes
    Transcription factor mechanistic analysis

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