Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

18.9K
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...
18.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A scalable speech coding scheme using compressive sensing and orthogonal mapping based vector quantization.

Heliyon·2019
Same author

A computer-aided diagnosis system for plus disease in retinopathy of prematurity with structure adaptive segmentation and vessel based features.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2019
Same author

Pectoral muscle identification in mammograms.

Journal of applied clinical medical physics·2011
Same author

Computer-aided identification of the pectoral muscle in digitized mammograms.

Journal of digital imaging·2009
Same author

A multi-level wavelet approach for automatic detection of epileptic spikes in the electroencephalogram.

Computers in biology and medicine·2008

Related Experiment Video

Updated: Oct 10, 2025

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR
10:27

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

Published on: July 30, 2011

23.4K

An Automated cDNA Microarray Image Analysis for the Determination of Gene Expression Ratios.

Steffy Maria Joseph, P S Sathidevi

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |December 15, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an automated cDNA microarray image analysis technique. It accurately segments spots and normalizes intensities for reliable gene expression ratio determination.

    More Related Videos

    Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
    13:14

    Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

    Published on: August 10, 2009

    11.8K
    Bacterial Gene Expression Analysis Using Microarrays
    29:41

    Bacterial Gene Expression Analysis Using Microarrays

    Published on: May 28, 2007

    8.9K

    Related Experiment Videos

    Last Updated: Oct 10, 2025

    Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR
    10:27

    Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

    Published on: July 30, 2011

    23.4K
    Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
    13:14

    Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

    Published on: August 10, 2009

    11.8K
    Bacterial Gene Expression Analysis Using Microarrays
    29:41

    Bacterial Gene Expression Analysis Using Microarrays

    Published on: May 28, 2007

    8.9K

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • cDNA microarray technology is crucial for gene expression profiling.
    • Accurate image analysis is essential for reliable microarray data.
    • Existing methods often lack full automation and robust segmentation.

    Purpose of the Study:

    • To develop a fully automated technique for cDNA microarray image analysis.
    • To improve the accuracy of spot segmentation and intensity extraction.
    • To enable reliable determination of gene expression ratios.

    Main Methods:

    • Automated preprocessing, gridding, and spot segmentation using TV-L1 denoising and centroid analysis.
    • Evaluation of segmentation accuracy using Mean Absolute Error (MAE), Coefficient of Variation (CV), Probability of Error (PE), and Discrepancy Distance (DD).
    • Background intensity correction, noisy spot flagging, LOWESS normalization, and gene expression ratio calculation.

    Main Results:

    • The proposed technique achieves high accuracy in segmenting spot regions.
    • Performance metrics demonstrate superior results compared to existing methods on both real and synthetic datasets.
    • Accurate normalization and gene expression ratio determination are achieved.

    Conclusions:

    • The developed automated technique offers a robust and efficient solution for cDNA microarray image analysis.
    • This method enhances the reliability of gene expression profiling.
    • It provides a valuable tool for genomic research and discovery.