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Related Experiment Video

Updated: Jul 29, 2025

Measurement of Energy Metabolism in Explanted Retinal Tissue Using Extracellular Flux Analysis

Measurement of Energy Metabolism in Explanted Retinal Tissue Using Extracellular Flux Analysis

Published on: January 7, 2019

FLUXestimator: a webserver for predicting metabolic flux and variations using transcriptomics data.

Zixuan Zhang^1,2, Haiqi Zhu^2,3, Pengtao Dang^2,4

¹College of Software, College of Computer Science and Technology, Jilin University, Changchun 130012, China.

Nucleic Acids Research

|May 22, 2023

Summary

FLUXestimator predicts single cell metabolic flux using transcriptomics data. This new tool aids in understanding disease-related metabolic heterogeneity and developing therapies.

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Last Updated: Jul 29, 2025

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Analyzing Ex Vivo Metabolic Flux in Splenic and Cardiac Macrophages and Bone Marrow Monocytes

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Published on: March 28, 2025

Area of Science:

Metabolic Engineering
Computational Biology
Systems Biology

Background:

Quantitative assessment of single cell fluxome is crucial for understanding metabolic heterogeneity in diseases.
Current laboratory-based single cell fluxomics methods are impractical, and existing computational tools lack single cell-level prediction capabilities.

Purpose of the Study:

To present FLUXestimator, an online platform for predicting metabolic fluxome and variations from single cell or general transcriptomics data.
To provide a web-based tool for predicting cell-/sample-wise metabolic flux and metabolite variations using transcriptomics data across multiple species.

Main Methods:

Implementation of a recently developed unsupervised approach, single cell flux estimation analysis (scFEA).
Utilization of a novel neural network architecture within the scFEA approach to estimate reaction rates from transcriptomics data.
Development of an online platform (webserver) and stand-alone tools for local use.

Main Results:

FLUXestimator enables prediction of metabolic fluxome at the single cell level using transcriptomics data.
The platform supports analysis of large sample-size transcriptomics data for human, mouse, and 15 other experimental organisms.
FLUXestimator is presented as the first web-based tool dedicated to predicting cell-/sample-wise metabolic flux and metabolite variations.

Conclusions:

FLUXestimator offers a novel computational approach to study metabolic heterogeneity in diseases.
The tool provides a new avenue for researchers to investigate metabolic variations at the single cell level.
FLUXestimator has the potential to facilitate the development of new therapeutic strategies by revealing metabolic insights.