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

23.0K
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...
23.0K
RNA-seq03:21

RNA-seq

12.6K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
12.6K
Next-generation Sequencing03:00

Next-generation Sequencing

101.7K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
101.7K

You might also read

Related Articles

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

Sort by
Same author

Multiobjective blood pump impeller optimization with three response surface methods and prototype stator casting for an integrated motor pump.

Scientific reports·2026
Same author

Deep learning-based neuroanatomical profiling reveals population-specific brain changes in multiple sclerosis: a large-scale Middle Eastern study.

BMC medical imaging·2026
Same author

AI-Driven Multi-parametric MS Lesion Analysis from T2-FLAIR Imaging: a Clinical Decision Support Framework for Neuroradiology.

Journal of imaging informatics in medicine·2026
Same author

Incorporating normal periventricular changes for enhanced pathological white matter hyperintensity segmentation: on multiclass deep learning approaches.

Biomedical engineering online·2026
Same author

A Multiple Sclerosis MRI Dataset with Tri-Mask Annotations for Lesion Segmentation.

Scientific data·2026
Same author

A Parameter-free unsupervised framework for fMRI data analysis using batch learning growing neural gas and spatial-temporal false positive control.

Computer methods and programs in biomedicine·2026

Related Experiment Video

Updated: Apr 5, 2026

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma
09:58

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

Published on: June 6, 2025

1.3K

Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

Hamidreza Saberkari1, Sheyda Bahrami1, Mousa Shamsi1

  • 1Department of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.

Journal of Medical Signals and Sensors
|August 19, 2015
PubMed
Summary
This summary is machine-generated.

Accurate DNA microarray image analysis is crucial for gene expression studies and cancer cell classification. This study presents a novel hybrid model for precise spot positioning, achieving 100% accuracy on noiseless images.

Keywords:
Breast cancerfuzzy clusteringgene expressionmicroarraynoise

More Related Videos

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization
16:37

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Published on: August 5, 2008

13.4K
High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries
11:22

High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries

Published on: August 12, 2019

19.3K

Related Experiment Videos

Last Updated: Apr 5, 2026

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma
09:58

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

Published on: June 6, 2025

1.3K
Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization
16:37

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Published on: August 5, 2008

13.4K
High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries
11:22

High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries

Published on: August 12, 2019

19.3K

Area of Science:

  • Genomics
  • Bioinformatics
  • Image Analysis

Background:

  • DNA microarrays enable simultaneous study of thousands of gene expressions.
  • Accurate spot positioning in microarray images is critical for reliable gene expression analysis and cell classification.
  • Existing methods face challenges in precisely locating spots, impacting data accuracy.

Purpose of the Study:

  • To develop and evaluate a novel hybrid model for accurate spot positioning in DNA microarray images.
  • To improve the segmentation quality of complementary DNA microarray images.
  • To enhance the classification of normal and abnormal (cancer) cells through precise microarray analysis.

Main Methods:

  • Preprocessing using nonlinear anisotropic diffusion filtering to remove noise and artifacts.
  • Spot center positioning via mathematical morphology operations.
  • Hybrid model combining Principle Component Analysis (PCA) and Spatial Fuzzy C-Means clustering (SFCM) with a Gaussian kernel for precise spot determination.

Main Results:

  • The proposed hybrid model achieved 100% accuracy in segmenting noiseless microarray cells.
  • The algorithm demonstrated 98% accuracy for noisy microarray cells.
  • The use of a Gaussian kernel in SFCM improved complementary DNA microarray segmentation quality.

Conclusions:

  • The novel hybrid PCA-SFCM model offers a highly accurate solution for DNA microarray image segmentation and spot positioning.
  • This method effectively addresses noise and artifacts, leading to improved gene expression analysis and cancer cell classification.
  • The algorithm's high accuracy on real microarray data validates its potential for robust biological research.