Dna Microchip Method
Dna Microchip Method - Related Videos
04:48
Automated Capillary Electrophoresis Based Fragment Size Distribution Analysis of cfDNA: A DNA Microchip-based Method to Study Size Distribution of DNA Fragments Isolated from Biofluids
0 Views •
2025
In this video, we analyze the size distribution of cell-free DNA or cfDNA fragments using automated capillary electrophoresis. This technique helps gain insights into the profile of DNA fragments released by cancer cells during apoptosis.
04:21
Microfluidic Capillary Electrophoresis for Fragment Sizing of PCR Products: A Microchip-Based Electrophoretic Separation Technique to Separate DNA Fragments Based on Size
0 Views •
2025
This video describes the microfluidic capillary electrophoresis technique to separate PCR amplicons based on their size. This technique helps in fragment sizing using fluorescent dyes and standard molecular size markers.
09:42
Fabrication of a Dipole-assisted Solid Phase Extraction Microchip for Trace Metal Analysis in Water Samples
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2016
The fabrication protocol of a dipole-assisted solid phase extraction microchip for the trace metal analysis is presented.
11:01
RNA-Associated Chromatin DNA-DNA Interaction Method
0 Views •
2026
Here, we present a protocol to capture RNA-associated chromatin DNA-DNA interactions for mapping RNA-related three-dimensional genome organization.
23:21
Silicon Microchips for Manipulating Cell-cell Interaction
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Cited by 7 •
2007
This article describes an experimental approach for dynamic regulation of cell-cell interactions between adherent cells on a micrometer scale. Manipulation of intercellular communication between hepatocytes and stromal cell is demonstrated. The developed platform enables investigation of cell-cell interactions in a variety of biological processes, including development and pathogenesis.
FAQs
Sequence specificity comes from matching each immobilized probe with a complementary nucleic acid sequence in the labeled sample. Hybridization retains matching material at the corresponding array location, while the measured fluorescent signal indicates whether that sequence is present or how strongly it is represented. This molecular selectivity lets many targets be assessed in parallel.
The sample type determines the biological question. Labeled DNA can support analysis of genetic variation, including mutations or copy-number changes, whereas labeled RNA provides information about gene activity through expression patterns. Keeping these readouts conceptually separate helps investigators interpret whether a tumor difference reflects altered sequence content or altered gene activity.
Fluorescence is not merely a positive-or-negative label: its measured level is used to estimate the amount of the matching sequence or the associated expression signal. Because each location corresponds to a sequence-specific probe, the resulting pattern across the array creates a molecular profile. That profile can then be compared between samples.
A typical analysis starts with a DNA or RNA sample prepared with a fluorescent label. The labeled material is brought into contact with the probe array so complementary sequences can hybridize. After binding, fluorescence is measured across the array, and the combined signals are analyzed as a profile of sequence presence or gene activity.
In cancer studies, investigators can compare molecular profiles from diseased and normal tissue to identify differences associated with the tumor. Expression changes may reveal altered gene activity, while DNA-based patterns can indicate mutations or copy-number changes. The comparison links array measurements to tumor biology rather than treating each fluorescent signal as an isolated result.
These profiles can help distinguish cancer subtypes by their molecular patterns and support biomarker discovery. A biomarker is a measurable molecular feature associated with a disease state or classification. In the cancer setting, the resulting information can contribute to diagnosis and treatment planning by connecting molecular tumor characteristics with clinically relevant decisions.