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

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...

You might also read

Related Articles

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

Sort by
Same author

Making Security Viral: Shifting Engineering Biology Culture and Publishing.

ACS synthetic biology·2022
Same author

Assessing Open-Ended Human-Computer Collaboration Systems: Applying a Hallmarks Approach.

Frontiers in artificial intelligence·2021
Same author

Pathogen metadata platform: software for accessing and analyzing pathogen strain information.

BMC bioinformatics·2016
Same author

Comprehensive Definition of the SigH Regulon of Mycobacterium tuberculosis Reveals Transcriptional Control of Diverse Stress Responses.

PloS one·2016
Same author

Characterization of a cAMP responsive transcription factor, Cmr (Rv1675c), in TB complex mycobacteria reveals overlap with the DosR (DevR) dormancy regulon.

Nucleic acids research·2015
Same author

Role of intragenic binding of cAMP responsive protein (CRP) in regulation of the succinate dehydrogenase genes Rv0249c-Rv0247c in TB complex mycobacteria.

Nucleic acids research·2015
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: May 30, 2026

ampliPHOX Colorimetric Detection on a DNA Microarray for Influenza
09:32

ampliPHOX Colorimetric Detection on a DNA Microarray for Influenza

Published on: June 9, 2011

Open-target sparse sensing of biological agents using DNA microarray.

Mojdeh Mohtashemi1, David K Walburger, Matthew W Peterson

  • 1Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org

BMC Bioinformatics
|August 2, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces an "open-target" biosensing approach using DNA microarrays and a mathematical model to detect multiple organisms. This method achieves high sensitivity and specificity with a reduced number of probes, advancing biosensor technology.

More Related Videos

Visual Detection of Multiple Nucleic Acids in a Capillary Array
08:56

Visual Detection of Multiple Nucleic Acids in a Capillary Array

Published on: November 15, 2017

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

Related Experiment Videos

Last Updated: May 30, 2026

ampliPHOX Colorimetric Detection on a DNA Microarray for Influenza
09:32

ampliPHOX Colorimetric Detection on a DNA Microarray for Influenza

Published on: June 9, 2011

Visual Detection of Multiple Nucleic Acids in a Capillary Array
08:56

Visual Detection of Multiple Nucleic Acids in a Capillary Array

Published on: November 15, 2017

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

Area of Science:

  • Biotechnology
  • Genomics
  • Bioinformatics

Background:

  • Traditional biosensors require specific reagents for each target organism, limiting adaptability.
  • An "open-target" biosensing strategy is proposed, utilizing a DNA microarray with non-specific probes.
  • This approach aims to detect organisms without prior knowledge of their specific sequences.

Purpose of the Study:

  • To develop and validate an "open-target" DNA microarray biosensing platform.
  • To demonstrate the capability of identifying multiple organisms in mixed samples.
  • To assess the sensitivity and specificity of the proposed biosensing method.

Main Methods:

  • A DNA microarray with 12,900 oligonucleotide probes was designed using statistical models from pathogenic prokaryotic genomes.
  • A multivariate mathematical model based on partial least squares regression (PLSR) was developed for organism detection.
  • A sampling algorithm was employed to identify a minimal set of probes for efficient detection.

Main Results:

  • The PLSR model successfully detected three test organisms in mixed samples with a mean R² of 0.76 and 95% confidence interval.
  • A sparse sampling approach identified 47 probes capable of detecting the test organisms with a mean R² of 0.77 and high specificity.
  • The system demonstrated a 6% false positive rate when using all probes, which was significantly reduced with sparse sampling.

Conclusions:

  • The "open-target" biosensing approach effectively identifies multiple organisms in mixed samples using a small, non-specifically designed DNA microarray.
  • The combination of a mathematical model and sparse probe sampling achieves high sensitivity and specificity.
  • This novel biosensing strategy aligns with the principles of sparse sensing, offering a more adaptable platform.