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: Jul 3, 2026

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper
07:38

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Published on: April 9, 2017

Interpretable spatial multi-omics data integration and dimensionality reduction with SpaMV.

Yang Liu1, Kexin Ma2, Haoran Xu2

  • 1Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China.

Nature Communications
|July 1, 2026
PubMed
Summary

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

The Liver-Testis Axis: Molecular Mechanisms and Clinical Implications.

International journal of molecular sciences·2026
Same author

Invas: an inversion-aware method for transcriptome assembly.

Nature communications·2026
Same author

Multi-modality Graph Representation Learning for Malignant Cell Identification from scRNA-seq using DeepMalignant.

bioRxiv : the preprint server for biology·2026
Same author

Restoration of Spirulina growth in recycled medium via a combined strategy of nutrient supplementation and flocculation treatment.

Bioresource technology·2026
Same author

High-quality phage assembly from metagenomes with PALACE.

Nature biotechnology·2026
Same author

Linoleic acid accelerates osteoarthritis progression in male rats by targeting iron-sulfur clusters to drive ferroptosis in chondrocytes.

Nature communications·2026

Spatial multi-omics integration methods can now better capture shared and distinct omics data using the new Spatial Multi-View (SpaMV) algorithm. This approach enhances biological insights and biomarker discovery from complex spatial datasets.

Area of Science:

  • Computational biology
  • Genomics
  • Systems biology

Background:

  • Spatial multi-omics technologies offer high-resolution molecular data.
  • Current integration methods often project diverse omics into a single latent space, losing unique information.
  • This loss limits the full potential of multi-omics analyses.

Purpose of the Study:

  • To develop a novel representation learning algorithm for spatial multi-omics data.
  • To explicitly capture both shared and omics-specific information.
  • To improve the interpretability and comprehensiveness of multi-omics data integration.

Main Methods:

  • Developed the Spatial Multi-View (SpaMV) representation learning algorithm.
  • SpaMV disentangles shared and omics-specific features from integrated spatial multi-omics data.

Related Experiment Videos

Last Updated: Jul 3, 2026

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper
07:38

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Published on: April 9, 2017

  • Evaluated performance on simulated and real-world datasets.

    • Main Results:

    • SpaMV achieved superior spatial domain clustering compared to existing methods.
    • The algorithm provides more interpretable dimensionality reduction for topic modeling.
    • SpaMV effectively identifies omics-specific biomarkers, outperforming current approaches.

    Conclusions:

    • SpaMV offers a more comprehensive and interpretable approach to spatial multi-omics data integration.
    • The method enhances the discovery of omics-specific biomarkers.
    • SpaMV unlocks deeper biological insights by preserving unique omics information.