Gene expression profiling designates the systematic determination of the pattern of genes expressed at the level of genetic transcription in a specific cell, tissue, or biological condition. Its defining operational feature is the parallel measurement of transcript abundance for thousands of genes simultaneously, generating a global quantitative description—a profile—of the transcriptional state of the biological sample rather than a measurement of any single transcript in isolation. The term encompasses the measurement of expressed RNA transcripts across defined biological states, including the comparison of differentially expressed transcripts among tissues, cells, strains, or experimental conditions ^[1]. Two principal technological platforms realize this parallel measurement: hybridization-based microarrays, in which labeled target sequences are annealed to ordered arrays of complementary oligonucleotide probes and the resulting signal intensities report relative transcript abundance ^[2][3], and sequencing-based RNA-Seq, in which the population of transcripts is converted to cDNA, sequenced in a massively parallel manner, and the resulting reads are mapped and counted to yield transcript-level quantification ^[4]. The conceptual scope of gene expression profiling is defined by its unit of analysis—the transcriptome, the complete set of RNA transcripts present in a cell or sample at a given moment—and by its output—a comparative, genome-scale expression pattern that links molecular information to cellular phenotype and function ^[1][4]. The profiling enterprise thus establishes a functional annotation of the genome in operation, capturing the subset of genes that is active, the relative levels of their expression, and the changes in these patterns that accompany physiological, developmental, or pathological states ^[5].