摘要
Gene expression profiling using cDNA or high-density oligonucleotide microarray contributes signifi cantly to our understanding on the transcriptome of a given biological condition. Using this technology, huge number of differentially-expressed genes of interest have been identified in a broad range of circumstances. Making sense biologically on these genes using the recently-improved functional annotation and data integration has leveraged our understanding in diseases and their biological mechanisms. However, understanding the codes encrypt- ed in the cis-aeting regulatory regions and gaining insights into the circuitry of functional regulatory networks on the genomic scale will require additional empirical data sets that are capable of revealing the cohorts or regulons of the transcription and the dynamic progression of molecular events responsible for certain biological function.
Gene expression profiling using cDNA or high-density oligonucleotide microarray contributes significantly to our understanding on the transcriptome of a given biological condition. Using this technology, huge number of differentially-expressed genes of interest have been identified in a broad range of circumstances.
