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 Video

Updated: Jun 10, 2026

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

Statistical methods for integrating multiple types of high-throughput data.

Yang Xie1, Chul Ahn

  • 1Division of Biostatistics, Department of Clinical Sciences, The Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Methods in Molecular Biology (Clifton, N.J.)
|July 24, 2010
PubMed
Summary
This summary is machine-generated.

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

Polypill for heart failure with reduced ejection fraction: the POLY-HF randomized trial.

Nature medicine·2026
Same author

Stress and cardiovascular disease: Testing a vigilance pathway in two contemporary theories.

Health psychology : official journal of the Division of Health Psychology, American Psychological Association·2026
Same author

Monoclonal antibodies targeting PCDH7 inhibit tumor growth and enhance immune responses in <i>KRAS</i>-mutant non-small cell lung cancer.

Science advances·2026
Same author

Involved nodal versus elective neck radiotherapy (INVERT) for head and neck squamous cell carcinoma: a prospective phase II randomized controlled trial protocol.

BMC cancer·2026
Same author

Sample Size Determination for Comparing Slopes in Cluster Randomized Trials With Longitudinal Measurements.

Statistics in medicine·2026
Same author

Undetected Weight Loss Associates With Upstaging in Cancer Patients.

Journal of cachexia, sarcopenia and muscle·2026
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Integrating diverse biomedical data, including sequencing and protein information, enhances research power. This study highlights the need for robust methods to combine heterogeneous data for deeper biological insights.

Area of Science:

  • Biomedical research
  • Bioinformatics
  • Data science

Background:

  • Large-scale omics data (sequencing, copy number, mRNA, protein) offer immense biomedical potential but present significant data management and analysis challenges.
  • Integrating diverse data types from multiple sources is crucial for increasing statistical power and achieving deeper biological understanding.

Purpose of the Study:

  • To illustrate the urgent need for reliable methods to integrate heterogeneous biomedical data.
  • To review recently developed statistical methods for integrative analysis.
  • To provide practical resources for integrative analysis.

Main Methods:

  • Illustrative examples from two biomedical research cases.
  • Review of statistical methods for integrative analysis (inference and classification).

Related Experiment Videos

Last Updated: Jun 10, 2026

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

  • Presentation of public databases and program code.

    • Main Results:

    • Demonstrated the critical need for robust data integration techniques.
    • Introduced and discussed various statistical approaches for combining heterogeneous data.
    • Highlighted accessible resources to aid practical implementation.

    Conclusions:

    • Effective integration of diverse biomedical data is essential for advancing research.
    • Development and application of advanced statistical methods are key to unlocking the potential of large-scale datasets.
    • Availability of public databases and code facilitates the adoption of integrative analysis.