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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Labeling DNA Probes03:31

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DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
Radioisotopes, fluorophores, or small molecule binding partners like biotin or digoxigenin, are the most widely used reporter tags for labeling DNA probes. These labels can be attached to the probe DNA molecule via...
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FISH - Fluorescent In-situ Hybridization02:07

FISH - Fluorescent In-situ Hybridization

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Fluorescence in situ hybridization, or FISH, was developed in the early 1980s and has quickly become one of the most widely used techniques in cytogenetics. Labeled probes are used to bind complementary DNA or RNA sequences on a chromosome or in a region within a cell. Earlier, the probes could only be obtained by cloning or reverse transcription of a DNA template. Currently, the probe oligonucleotides can be synthesized synthetically. Additionally, with the advancement of optical techniques,...
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A Microfluidic-based Electrochemical Biochip for Label-free DNA Hybridization Analysis
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A Microfluidic-based Electrochemical Biochip for Label-free DNA Hybridization Analysis

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Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB.

Ahsan Munir1, Hassan Waseem2, Maggie R Williams3

  • 1Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48823,USA. ahsan.muneer@gmail.com.

Microarrays (Basel, Switzerland)
|May 31, 2017
PubMed
Summary
This summary is machine-generated.

A new computer model accurately predicts DNA hybridization kinetics on microfluidic biochips. This advancement enhances sensitivity and speed for medical diagnostics and other applications using nucleic acid detection.

Keywords:
DNA biochipsFEMLABhybridization kineticsmicrofluidicsvancomycin resistance genes

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Area of Science:

  • Biotechnology
  • Bioengineering
  • Molecular Diagnostics

Background:

  • Microfluidic DNA biochips are vital for medical diagnostics, drug discovery, food safety, and agriculture.
  • Analyzing nucleic acid biomarkers requires understanding DNA binding kinetics on biochip surfaces.
  • Predicting hybridization kinetics is crucial for optimizing sensitivity and speed in microfluidic assays.

Purpose of the Study:

  • To develop a computational model for designing and optimizing flow-through microfluidic DNA biochips.
  • To simulate DNA transport and hybridization kinetics on biochip surfaces.
  • To correlate predicted hybridization kinetics with experimental data.

Main Methods:

  • Utilized a finite element method (FEMLAB) to create a numerical model.
  • Simulated fluid flow, convection, and diffusion within the microfluidic chamber and on the reaction surface.
  • Investigated parameters like concentration, rate constants, flow rate, and temperature.

Main Results:

  • The model successfully predicted DNA hybridization kinetics and signal intensities for eighteen probes targeting vancomycin resistance genes (VRGs).
  • Predicted signal intensities and hybridization kinetics showed a strong correlation with experimental results (R² = 0.8131).
  • Key parameters influencing hybridization rate were identified.

Conclusions:

  • The developed numerical model is effective for optimizing microfluidic biochip design.
  • Accurate prediction of hybridization kinetics can improve biochip sensitivity and assay performance.
  • This approach supports the advancement of nucleic acid-based biomarker detection technologies.