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

You might also read

Related Articles

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

Sort by
Same author

Ginkgo biloba Extract Attenuates the Disruption of Pro- and Anti-inflammatory Balance of Peripheral Blood in Arsenism Patients by Decreasing Hypermethylation of the Foxp3 Promoter Region.

Biological trace element research·2022
Same author

In utero exposure to methylmercury impairs cognitive function in adult offspring: Insights from proteomic modulation.

Ecotoxicology and environmental safety·2022
Same author

LC/MS/MS-Based Liver Metabolomics to Identify Chronic Liver Injury Biomarkers Following Exposure to Arsenic in Rats.

Biological trace element research·2022
Same author

Corrigendum to "SFPQ is involved in regulating arsenic-induced oxidative stress by interacting with the miRNA-induced silencing complexes" [Environ. Pollut. 261 (2020) 114160].

Environmental pollution (Barking, Essex : 1987)·2021
Same author

Computational Systems Pharmacology, Molecular Docking and Experiments Reveal the Protective Mechanism of Li-Da-Qian Mixture in the Treatment of Glomerulonephritis.

Journal of inflammation research·2021
Same author

Characteristics and phylogenetic analysis of the complete chloroplast genome of <i>Lilium concolor</i> Salisb. (Liliaceae) from Jilin, China.

Mitochondrial DNA. Part B, Resources·2021
Same journal

Synergistic Geroprotectors Mapping through Systems Machine Learning and Graph Neural Networks.

Omics : a journal of integrative biology·2026
Same journal

<i>ENTPD2</i> Transcript-Protein Divergence in Colorectal Cancer and Its Association with miR-708-5p: An Integrative Analysis.

Omics : a journal of integrative biology·2026
Same journal

Integrated Bioinformatics and Molecular Docking Analysis Reveals Potential Mechanisms of Coptidis Rhizoma in Intervertebral Disc Degeneration.

Omics : a journal of integrative biology·2026
Same journal

Site-Specific Phosphoproteomics Uncovers Potential Regulatory Networks of NEK4 in DNA Damage Response and Cancer Progression.

Omics : a journal of integrative biology·2026
Same journal

Network-Based Multiomics Integration Reveals Immunometabolic Convergence Between COVID-19 and Pulmonary Arterial Hypertension.

Omics : a journal of integrative biology·2026
Same journal

Procaterol Enhances Cisplatin-Induced Cytotoxicity via Apoptosis, Oxidative Stress, and Cell Cycle Arrest in Breast and Cervical Cancer Cells.

Omics : a journal of integrative biology·2026
See all related articles

Related Experiment Video

Updated: May 8, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

Cell metabolomics.

Aihua Zhang1, Hui Sun, Hongying Xu

  • 1National TCM Key Laboratory of Serum Pharmacochemistry, Key Laboratory of Chinmedomics, Key Pharmacometabolomics Platform of Chinese Medicines, and Heilongjiang University of Chinese Medicine , Harbin, China .

Omics : a Journal of Integrative Biology
|August 31, 2013
PubMed
Summary
This summary is machine-generated.

Cell metabolomics uses advanced techniques to analyze cellular metabolism, offering insights into cell function and disease. This approach identifies biomarkers for various conditions in the postgenomics era.

More Related Videos

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
07:34

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

Related Experiment Videos

Last Updated: May 8, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
07:34

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

Area of Science:

  • Biochemistry
  • Systems Biology
  • Genomics

Background:

  • Metabolomics analyzes endogenous biochemicals to understand cellular metabolic pathways.
  • Cellular metabolism is integral to all cell functions, reflecting the cell's phenotype.
  • Cell metabolomics is a key emerging field in post-genomics biology and systems medicine.

Purpose of the Study:

  • To review recent advancements in cell metabolomics.
  • To explore the characterization and interpretation of cellular metabolomes.
  • To discuss the role of small molecule metabolites in pathophysiological and clinical contexts.

Main Methods:

  • Sample preparation and metabolite extraction.
  • Metabolic profiling using Mass Spectrometry (MS) or Nuclear Magnetic Resonance (NMR) spectroscopy.
  • Bioinformatics for pattern recognition and data analysis, followed by metabolite identification.

Main Results:

  • Identification of putative biomarkers and molecular targets.
  • Integration of biomarkers into metabolic networks for biochemical insights.
  • Characterization of cellular metabolomes across diverse pathophysiological states.

Conclusions:

  • Cell metabolomics provides a powerful approach to understand cellular function and disease.
  • It offers advantages over existing methods in the post-genomics era.
  • This field is crucial for advancing systems medicine and identifying novel therapeutic targets.