Microarray Profiling
Microarray Profiling - Related Videos
08:29
Expression Profiling with Microarrays
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2023
Microarrays are important tools for profiling gene expression, and are based on complementary binding between probes that are attached to glass chips and nucleic acids derived from samples. Using these arrays, scientists can simultaneously evaluate the expression of thousands of genes. In addition, the expression profiles of different cells or tissue types can be compared, allowing researchers to deduce how the expression of different genes change during biological processes, and thus gain...
12:30
Glycan Profiling of Plant Cell Wall Polymers using Microarrays
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Cited by 26 •
2012
A technique called Comprehensive Microarray Polymer Profiling (CoMPP) for the characterisation of plant cell wall glycans is described. This method combines the specificity of monoclonal antibodies directed to defined glycan-epitopes with a miniature microarray analytical platform allowing screening of glycan occurrence in a broad range of biological contexts.
10:27
Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR
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Cited by 12 •
2011
Microarray analysis was conducted to determine genetic expression profiles in C. elegans, and real-time PCR was used to validate and quantify microarray data.
05:21
A Peptide Microarray Technology for Specificity Profiling of Antibodies
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2025
This video demonstrates a technique that applies peptide microarray technology to profile the specificity of antibodies recognizing post-translational modifications (PTMs) on histone peptides. A microarray slide containing immobilized fluorophore-conjugated histone peptides with known PTM combinations is treated with target PTM-specific antibodies. This process helps identify the antibody's specificity for the target and its potential cross-reactivity with non-target PTMs.
15:17
Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
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Cited by 19 •
2011
We described a procedure for the disaggregation of colorectal cancer (CRC) to produce viable single cells, which are then captured on customized antibody microarrays recognizing surface antigens (DotScan CRC microarray). Sub-populations of cells bound to the microarray can be profiled by fluorescence multiplexing using monoclonal antibodies tagged with fluorescent dyes.
FAQs
Sequence complementarity determines which immobilized probe captures a labeled transcript-derived molecule. The assay uses labeled complementary DNA or RNA, allowing each molecule to bind probes representing matching sequences on the chip. Fluorescence recorded at a probe location therefore connects the measured signal to a particular transcript, enabling transcript-by-transcript comparisons across biological samples.
Normalization is essential because raw fluorescence values are not directly comparable until measurements are placed on a common analytical basis. After normalization, differences in signal can be interpreted as relative differences in transcript abundance between samples rather than as unadjusted chip-level measurements. This step supports more reliable comparisons among experimental groups.
A stronger signal at a probe indicates greater relative abundance of the matching transcript in that sample after normalization. The result is a comparative expression measurement tied to sequences represented by the chip, not a direct inventory of every RNA molecule. This distinction helps researchers interpret profiles as patterns of relative transcript abundance.
In neuroscience, profiles can be organized around biologically distinct comparisons, including brain regions, cell types, developmental stages, and disease states. Examining which transcripts differ across these groups helps identify molecular expression patterns associated with neural context. The approach relates transcript-level variation to differences in cellular states, development, or pathology rather than treating the brain as molecularly uniform.
A basic workflow begins by selecting biological samples for comparison, applying labeled complementary DNA or RNA to the chip, and allowing sequence-complementary binding to immobilized probes. Fluorescence is then measured at probe locations, followed by normalization of the resulting signals. Researchers compare the normalized profiles to identify transcript-expression differences between samples.
Microarray Profiling can produce expression signatures that reveal altered pathways associated with particular neural samples or conditions. These signatures support biomarker discovery and help guide hypotheses about neural function and pathology. By comparing molecular patterns across regions, cell types, developmental stages, or disease states, researchers can connect transcript differences with broader questions in brain biology.