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

Patient-specific guides and osteosynthesis versus CAD/CAM occlusal splints in orthognathic surgery: a systematic review and meta-analysis of accuracy, operative time, and complications.

BMC oral health·2026
Same author

Application of Cell-Free DNA Barcode-Enabled Single-Molecule Test for Non-Invasive Prenatal Testing of α-Thalassemia and β-Thalassemia.

Journal of clinical laboratory analysis·2026
Same author

Coacervates of Lactoferrin with Resistant Dextrin via Noncovalent Interaction for Enhanced Thermal Stability, Interface Characteristics and Docosahexaenoic Acid (DHA) Encapsulation.

Food science of animal resources·2026
Same author

Whole Genome Sequencing and Genetic Variation Analysis of Parry-Romberg Syndrome.

The Journal of craniofacial surgery·2026
Same author

Identification of a master regulator Msd1 that governs meiotic entry in a global basidiomycete pathogen.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

GM-CSF and IL-1α secreted by cryopreserved porcine skin promote angiogenesis in burn wounds by activating the JAK2/STAT3 pathway.

American journal of translational research·2026

Related Experiment Video

Updated: Aug 16, 2025

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

3.8K

A Comprehensive Mass Spectrometry-Based Workflow for Clinical Metabolomics Cohort Studies.

Zhan Shi1, Haohui Li1, Wei Zhang2

  • 1Metanotitia Inc., No 59. Gaoxin South 9th Road, Yuehai Street, Nanshan District, Shenzhen 518056, China.

Metabolites
|December 23, 2022
PubMed
Summary
This summary is machine-generated.

This study presents a standardized workflow for clinical metabolomics, addressing challenges in data complexity and metabolite identification. The validated approach enhances the reliability of metabolomic analysis for disease prediction and diagnosis.

Keywords:
GC-MSLC-MSclinical cohortdata modelingdata normalizationmetabolomicsquality control

More Related Videos

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes
08:23

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

Published on: August 6, 2018

11.5K
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

12.8K

Related Experiment Videos

Last Updated: Aug 16, 2025

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

3.8K
2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes
08:23

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

Published on: August 6, 2018

11.5K
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

12.8K

Area of Science:

  • Metabolomics
  • Clinical Chemistry
  • Biomarker Discovery

Background:

  • Metabolomics offers comprehensive analysis of biological systems for disease prediction, diagnosis, and prognosis.
  • Widespread clinical implementation is hindered by challenges including data complexity, metabolite identification, and reproducibility.

Purpose of the Study:

  • To establish a comprehensive and standardized workflow for clinical metabolomics.
  • To address key challenges in sample handling, data acquisition, processing, and analysis.

Main Methods:

  • Standardized sample collection and preparation across multiple clinical sites.
  • Quality control (QC) samples and multiple mass spectrometry (MS) platforms (GC-MS, LC-MS polar, LC-MS lipid) for data acquisition.
  • Compound identification using commercial software and in-house libraries (PAppLineTM, UlibMS), batch effect removal (NormAE), and biomarker identification with tree-based models (random forest, AdaBoost, XGBoost).

Main Results:

  • Strict adherence to standardized operation procedures (SOP) ensured sample quality.
  • Integration of QC samples and advanced analytical techniques improved MS performance and metabolite identification.
  • Deep learning and tree-based modeling effectively removed batch effects and identified potential biomarkers, validated by F1 score and a case study.

Conclusions:

  • The developed workflow provides a reliable and reproducible method for clinical metabolomics.
  • This standardized approach facilitates accurate disease prediction, diagnosis, and prognosis.
  • The workflow's validation through a case study demonstrates its practical utility in clinical settings.