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

Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...

You might also read

Related Articles

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

Sort by
Same author

A pilot translational study of neoadjuvant fulvestrant plus abemaciclib in women with advanced low-grade serous carcinoma.

Nature communications·2026
Same author

scDeepAPA: a deep learning framework for single-cell alternative polyadenylation identification.

Briefings in bioinformatics·2026
Same author

Somatic variant detection in normal tissues from single-cell sequencing data.

bioRxiv : the preprint server for biology·2026
Same author

VIRSE: a variational Bayesian framework for RNA structural ensemble inference.

Briefings in bioinformatics·2026
Same author

Glycosphingolipids regulate phosphatidylserine transport machinery that operates at ER-PM contact sites.

Nature communications·2026
Same author

Socioeconomic and Clinical Determinants Driving Access to BRCA Genetic Testing in Cancer : A Case-Control Study Using Observational Electronic Health Records Across Multiple Sites.

medRxiv : the preprint server for health sciences·2026
Same journal

ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.

Nature methods·2026
Same journal

RNAbpFlow: base pair-augmented SE(3) flow matching for conditional RNA 3D structure generation.

Nature methods·2026
Same journal

Spatio-DARLIN enables robust and efficient in situ lineage tracing in mice at single-cell resolution.

Nature methods·2026
Same journal

EasyGrid: a versatile platform for automated cryo-EM sample preparation and quality control.

Nature methods·2026
Same journal

3D pathology-guided microdissection.

Nature methods·2026
Same journal

Derivation of elephant induced pluripotent stem cells.

Nature methods·2026
See all related articles

Related Experiment Video

Updated: Jun 21, 2026

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

17.3K

A visual-omics foundation model to bridge histopathology with spatial transcriptomics.

Weiqing Chen1,2, Pengzhi Zhang1,3,4,5, Tu N Tran1,3,4,5

  • 1Center for Bioinformatics and Computational Biology, Houston Methodist Research Institute, Houston, TX, USA.

Nature Methods
|May 29, 2025
PubMed
Summary
This summary is machine-generated.

We developed OmiCLIP, a novel visual-omics foundation model, integrating tissue histology images with transcriptomic data for advanced computational biology. Our Loki platform enables accurate spatial transcriptomics analysis and gene expression prediction.

More Related Videos

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.0K
Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics
07:43

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics

Published on: May 3, 2024

3.3K

Related Experiment Videos

Last Updated: Jun 21, 2026

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

17.3K
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.0K
Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics
07:43

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics

Published on: May 3, 2024

3.3K

Area of Science:

  • Computational biology
  • Bioinformatics
  • Genomics

Background:

  • Omics technologies like single-cell RNA sequencing and spatial transcriptomics generate detailed genomic data.
  • Current computational models often analyze omics data or image data separately, hindering integrated analysis.
  • Integrating histological images with transcriptomic data is crucial for a comprehensive understanding of biological systems.

Purpose of the Study:

  • To develop a foundation model, OmiCLIP, that integrates hematoxylin and eosin (H&E) stained tissue images with transcriptomic data.
  • To create the Loki platform, built upon OmiCLIP, to provide a suite of tools for visual-omics analysis.
  • To enable accurate spatial transcriptomics gene expression prediction directly from H&E images.

Main Methods:

  • Developed OmiCLIP, a visual-omics foundation model, by linking H&E images and transcriptomic data from Visium tissue patches.
  • Transformed transcriptomic data into 'sentences' by concatenating top-expressed gene symbols per patch.
  • Curated a large dataset of 2.2 million paired tissue images and transcriptomic data across 32 organs for model training.
  • Built the Loki platform with functionalities including tissue alignment, annotation, cell-type decomposition, and retrieval.

Main Results:

  • OmiCLIP successfully integrates histology and transcriptomics, trained on a large-scale dataset.
  • The Loki platform demonstrated consistent accuracy and robustness across 5 simulations and 23 diverse datasets (19 public, 4 in-house).
  • Loki outperforms 22 state-of-the-art models in various visual-omics tasks.

Conclusions:

  • OmiCLIP and the Loki platform represent a significant advancement in integrating imaging and omics data in computational biology.
  • This integrated approach enhances the analysis of spatial transcriptomics and gene expression.
  • Loki provides a powerful and versatile tool for researchers in genomics and bioinformatics.