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 Experiment Videos

[Integrating obtained knowledge from transcriptome data by a new framework for data analysis].

Tomokazu Konishi1

  • 1Faculty of Bioresource Sciences, Akita Prefectural University.

Rinsho Byori. the Japanese Journal of Clinical Pathology
|February 28, 2006
PubMed
Summary

Microarray analysis accuracy is low due to data analysis methods. A new parametric framework improves transcriptome data reproducibility and enables better genome information decoding.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Challenges and Future Directions in Lipoprotein Measurement for Atherosclerosis Prevention and Treatment.

International journal of molecular sciences·2025
Same author

Distinctive features of lipoprotein profiles in stroke patients.

PloS one·2023
Same author

Theanine, a Tea-Leaf-Specific Amino Acid, Alleviates Stress through Modulation of Npas4 Expression in Group-Housed Older Mice.

International journal of molecular sciences·2023
Same author

Human lipoproteins comprise at least 12 different classes that are lognormally distributed.

PloS one·2022
Same author

Mutations in SARS-CoV-2 are on the increase against the acquired immunity.

PloS one·2022
Same author

Continuous mutation of SARS-CoV-2 during migration via three routes at the beginning of the pandemic.

PeerJ·2022

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Context:

  • Microarray analysis measures transcriptome data to study genome information.
  • Current data analysis methods limit accuracy and reproducibility in comparative transcriptomics.
  • Sharing and integrating transcriptome data is crucial for advancing biological knowledge.

Purpose:

  • To critically evaluate existing microarray analysis frameworks.
  • To introduce a novel parametric framework for microarray data analysis.
  • To demonstrate the improved performance of the new framework using GeneChip data.

Summary:

  • Existing microarray analysis frameworks suffer from arbitrariness and lack of falsifiability, leading to low accuracy and reproducibility.
  • A new parametric framework is proposed, addressing these limitations and offering a more robust approach to analyzing transcriptome data.

Related Experiment Videos

  • Comparative analysis using GeneChip data shows enhanced stability in log-ratio measurements and improved reproducibility with the new framework.

    • Impact:

    • The developed framework offers a more reliable method for analyzing quantitative genome information from transcriptomes.
    • Improved data analysis facilitates better understanding of cellular states and differences between biological conditions.
    • This work contributes to the advancement of reproducible and accurate research in genomics and bioinformatics.