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

Peptide Identification Using Tandem Mass Spectrometry

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

You might also read

Related Articles

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

Sort by

Same author

Evaluation of metabolite biomarker candidates in detecting HCC in patients with liver cirrhosis.

Metabolomics : Official journal of the Metabolomic Society·2026

Same author

Glycoproteome Profiling of Human Serum for Hepatocellular Carcinoma Biomarker Discovery.

Journal of proteome research·2026

Same author

Integrated multi-omics reveals adaptive anti-oxidant remodeling in early alcohol-associated liver disease.

bioRxiv : the preprint server for biology·2026

Same author

Proteomic profiling of olfactory exfoliates from people with subjective cognitive complaints reveal networks of olfactory biomarkers of cognitive performance.

Frontiers in aging neuroscience·2026

Same author

Wearable sensors for monitoring drug pharmacokinetics in patients with Parkinson's disease.

Scientific reports·2026

Same author

Sex-specific effects of acetylation on tauopathy in aging htau mice.

Scientific reports·2026

Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 31, 2026

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

Preprocessing and Analysis of LC-MS-Based Proteomic Data.

Tsung-Heng Tsai^1,2, Minkun Wang^3,4, Habtom W Ressom³

¹Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, 20057, USA. thtsai@vt.edu.

Methods in Molecular Biology (Clifton, N.J.)

|November 1, 2015

Summary

This summary is machine-generated.

This study details liquid chromatography-mass spectrometry (LC-MS) data preprocessing for proteomics. It covers challenges and provides a step-by-step guide for untargeted proteomic analysis and multiple reaction monitoring.

Keywords:

Data preprocessing Label-free Liquid chromatography-mass spectrometry (LC-MS)Multiple reaction monitoring (MRM )Proteomics

More Related Videos

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Published on: November 17, 2019

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Published on: April 1, 2017

Related Experiment Videos

Last Updated: Mar 31, 2026

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Published on: November 17, 2019

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Published on: April 1, 2017

Area of Science:

Proteomics
Analytical Chemistry
Biochemistry

Background:

Liquid chromatography coupled with mass spectrometry (LC-MS) is a standard technique for protein expression profiling.
Accurate LC-MS data preprocessing is essential for reliable proteomic analysis.
Untargeted proteomic studies generate complex datasets requiring rigorous data handling.

Purpose of the Study:

To provide a comprehensive overview of LC-MS data preprocessing in proteomics.
To highlight common challenges encountered during LC-MS data analysis.
To present a practical, step-by-step example of data analysis for untargeted proteomic studies.

Main Methods:

Focus on data preprocessing techniques for LC-MS proteomics.
Illustrate analysis of untargeted LC-MS proteomic data.
Discuss procedures for subsequent multiple reaction monitoring (MRM) analysis.

Main Results:

Detailed explanation of critical LC-MS data preprocessing steps.
Identification of key challenges and potential solutions in data analysis.
Guidance on integrating untargeted profiling with targeted MRM analysis.

Conclusions:

Effective LC-MS data preprocessing is fundamental for accurate protein quantification.
Addressing preprocessing challenges improves the robustness of proteomic findings.
The presented methodology facilitates comprehensive proteomic profiling and targeted validation.