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

Longitudinal characterization of gait and balance recovery over 1 year using instrumented analysis in a school-aged child with ischemic stroke: a case report.

Journal of medical case reports·2026
Same author

Cryo-EM structure of the native assembled Mfa type V pilus from the periodontal pathogen Porphyromonas gingivalis.

Communications biology·2026
Same author

A commercial-scale high-throughput near-infrared transmission spectroscopy system for full inspection of active pharmaceutical ingredient content in all tablets.

International journal of pharmaceutics·2025
Same author

Use of tocilizumab to treat IgA nephropathy complicated by idiopathic multicentric Castleman disease: a case report.

BMC nephrology·2025
Same author

OmpA_C-Like Domain of PorE Is Essential for PorE Function in the Type IX Secretion System (T9SS) of Porphyromonas gingivalis and Some T9SS Cargo Proteins Are Secreted in a PorE-Independent Manner.

Microbiology and immunology·2025
Same author

Microvascular decompression for glossopharyngeal neuralgia using the transcondylar fossa approach: long-term follow-up results.

Neurosurgical focus·2025
Same journal

Thymidylate synthase inhibitory drugs induce p53-dependent pathways differently.

PloS one·2026
Same journal

Top-down and bottom-up attention for joint pattern classification and reconstruction.

PloS one·2026
Same journal

Short- and long-term scaling behavior of blood pressure and pulse arrival time during sleep in healthy controls and patients with obstructive sleep apnea.

PloS one·2026
Same journal

Double DQN-based secrecy energy efficiency and fairness performance in IRS-assisted NOMA systems with friendly jamming.

PloS one·2026
Same journal

10 recommendations for strengthening citizen science for improved societal and ecological outcomes: A co-produced analysis of challenges and opportunities in the 21st century.

PloS one·2026
Same journal

Paying in public: Peer effects, impression management, and willingness to pay on digital payment platforms.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Jun 28, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Coincidence between transcriptome analyses on different microarray platforms using a parametric framework.

Tomokazu Konishi1, Fumikazu Konishi, Shigeru Takasaki

  • 1Department of Bioresource Sciences, Akita Prefectural University, Shimosinjyo Nakano, Akita, Japan. konishi@akita-pu.ac.jp

Plos One
|October 30, 2008
PubMed
Summary
This summary is machine-generated.

A new parametric framework standardizes transcriptome data analysis across different microarray platforms. This approach ensures consistent gene expression results, enhancing data reliability and comparability in research.

More Related Videos

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs
10:28

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

Published on: April 14, 2015

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Related Experiment Videos

Last Updated: Jun 28, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs
10:28

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

Published on: April 14, 2015

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Microarray platforms are crucial for transcriptome analysis but often yield inconsistent results due to platform-specific analytical frameworks.
  • Discrepancies in data analysis frameworks undermine the reliability and comparability of findings across different studies.
  • Existing analytical frameworks lack universality, leading to doubts about the validity of collected transcriptome data.

Purpose of the Study:

  • To introduce a novel parametric framework for transcriptome data analysis.
  • To demonstrate the framework's ability to produce coincident results across different microarray platforms.
  • To enhance the universality and reliability of transcriptome data analysis.

Main Methods:

  • A parametric framework employing a strict normalization model was developed.
  • The framework normalizes microarray data based on a common statistical characteristic.
  • Data from slide-glass-type chips and GeneChip platforms were analyzed using the proposed model.

Main Results:

  • The parametric framework yielded coincident results when applied to data from different microarray platforms.
  • Normalization based on a linear relationship with a statistical model ensured consistency.
  • Expressional changes and selected genes were consistent across platforms, indicating superior universality.

Conclusions:

  • The proposed parametric framework offers a universal approach to transcriptome data analysis.
  • This method significantly improves the reliability and comparability of data obtained from diverse microarray platforms.
  • The framework addresses inconsistencies in transcriptome studies, paving the way for more robust genomic research.