Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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

Novel and emerging anesthetic drugs for the treatments of major depression: a comprehensive review of efficacy, mechanism, and outlook.

Frontiers in psychiatry·2025

Same author

Impact of delayed cord clamping and minimally invasive surfactant administration on outcomes in premature infants with neonatal respiratory distress syndrome at less than 30 weeks gestation: a NICU quality improvement study.

Frontiers in pediatrics·2025

Same author

Analysis of error profiles of indels and structural variants in deep-sequencing data.

Cell genomics·2025

Same author

CanID: A Robust and Accurate RNA-seq Expression-based Diagnostic Classification Scheme for Pediatric Malignancies.

Genomics, proteomics & bioinformatics·2025

Same author

Parental burnout as a mediator between fathers' parenting stress and preschoolers' emotional-behavioral problems: an urban-rural comparative study.

BMC psychology·2025

Same author

Fast and sensitive detection of targeted gene fusions using frequency minimizers and fuzzy pattern matching with Fuzzion2.

Cell reports methods·2025

Same journal

Vascular RhoJ Is an Effective and Selective Target for Tumor Angiogenesis and Vascular Disruption.

Cancer cell·2026

Same journal

Intratumoral B cells under stress.

Cancer cell·2026

Same journal

Chronic stress unleashes an intratumor phage-fibroblast-B cell circuit to promote tumor growth.

Cancer cell·2026

Same journal

Molecular phenotypes and spatial archetypes: A new framework for cancer-associated fibroblasts.

Cancer cell·2026

Same journal

OpenIO: An open framework for AI-native immunotherapy.

Cancer cell·2026

Same journal

From prediction to interpretation in computational pathology.

Cancer cell·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 2, 2025

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

Published on: June 7, 2018

Decoding tumor microenvironments through artificial tumor transcriptomes.

Liqing Tian¹, Jinghui Zhang¹

¹Department of Computational Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA.

|August 9, 2022

Summary

This summary is machine-generated.

Researchers developed a machine-learning method to reconstruct tumor microenvironments (TMEs) from cell data. This accurate approach allows for systematic TME investigation in research and clinical settings.

More Related Videos

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

Published on: September 20, 2016

Related Experiment Videos

Last Updated: Sep 2, 2025

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

Published on: June 7, 2018

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

Published on: September 20, 2016

Area of Science:

Oncology
Computational Biology
Bioinformatics

Background:

Tumor microenvironments (TMEs) are complex ecosystems crucial for cancer progression.
Accurate reconstruction of TMEs is essential for understanding tumor behavior and developing therapies.
Current methods for TME analysis face challenges in scalability and accuracy.

Purpose of the Study:

To present a novel machine-learning-based approach for reconstructing tumor microenvironments (TMEs).
To enable systematic and accurate investigation of TMEs in both research and clinical settings.

Main Methods:

Developed a machine-learning model trained on millions of artificial transcriptomes.
The model is designed to handle admixed cell populations within transcriptomic data.
Extensive validation was performed to demonstrate the approach's high accuracy.

Main Results:

The machine-learning approach accurately reconstructs tumor microenvironments.
The method demonstrates high performance across diverse simulated datasets.
Validation confirms the utility of the approach for real-world applications.

Conclusions:

This machine-learning-based method offers a powerful tool for TME reconstruction.
The approach facilitates systematic TME analysis, advancing cancer research.
Potential applications include improved diagnostics and therapeutic strategies in oncology.