Microarraybased

Microarray-based methods use a solid surface, such as a glass slide, onto which thousands to millions of probes are immobilized. In many assays, labeled target molecules from a sample hybridize to complementary probes, and the resulting signals are detected by a scanner. The measured intensities correspond to the abundance or presence of specific sequences, variants, or proteins, enabling high-throughput analysis of complex biological samples.

The platforms and probe types vary. DNA microarrays are the most common, featuring oligonucleotide or cDNA probes for applications such as gene-expression profiling, single-nucleotide polymorphism (SNP) genotyping, and copy-number variation analysis. CGH (comparative genomic hybridization) arrays compare two genomes to identify chromosomal gains and losses. Other microarrays target epigenetic marks, such as DNA methylation, or proteins, using antibody- or ligand-based capture on the surface. More recently, protein and peptide microarrays have been developed to study protein interactions, immune responses, and biomarker panels.

Applications of microarray-based approaches include transcriptome-wide gene expression analysis, identification of disease-associated variants, pharmacogenomics, molecular diagnostics, and biomarker discovery. They enable broad surveys of biological states and responses, often in a relatively short time and at lower per-assay costs for large sample sets, compared with conventional methods.

Data processing is a critical component, typically involving background correction, normalization, and statistical analysis to identify meaningful changes or differences. Limitations include cross-hybridization and a limited dynamic range, dependence on known sequences, and the need for careful design and validation. With the rise of next-generation sequencing, some uses of microarray-based methods have declined, but they remain in use for targeted assays and legacy data analysis.