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

Peptide Identification Using Tandem Mass Spectrometry01:33

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

ESCRT-0 regulates AMPA receptor currents and Ca <sup>2+</sup> - dependent signaling.

bioRxiv : the preprint server for biology·2026
Same author

Vaccination elicits HIV broadly neutralizing antibodies in primates.

Nature·2026
Same author

Translating Innovation to Clinic: End-to-End Bioprocess Development and cGMP Manufacturing of N332-GT5 HIV Vaccine Candidate for First-in-Human Trials HVTN144.

bioRxiv : the preprint server for biology·2026
Same author

Mass Spectrometry Imaging in ACS Journals.

ACS measurement science au·2026
Same author

Rapid Histone Post-Translational Modification Analysis Using Alternative Proteases and Tandem Mass Tags.

Analytical chemistry·2026
Same author

Fungal Extracellular Vesicles are Recoverable Across Variable Ultracentrifugation Speeds but Display Species-specific Profiles of Sedimentation.

The Journal of membrane biology·2026
Same journal

iMUT-seq mapping of DSB-induced mutations with high sensitivity at single-nucleotide resolution.

Nature protocols·2026
Same journal

An assay to quantify sexual commitment and stage conversion in the human malaria parasite Plasmodium falciparum.

Nature protocols·2026
Same journal

Author Correction: Direct inoculation of bioreactor-controlled stirred suspension culture with cryopreserved human pluripotent stem cells.

Nature protocols·2026
Same journal

High-throughput measurements of protein domain functions using magnetic separation.

Nature protocols·2026
Same journal

Inducing physiological polarity and performing gene editing using CRISPR-Cas9 in human trophoblast organoids.

Nature protocols·2026
Same journal

Photocatalytic low-temperature defluorination of PTFE.

Nature protocols·2026
See all related articles

Related Experiment Video

Updated: Jun 18, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

12.1K

Simple, efficient and thorough shotgun proteomic analysis with PatternLab V.

Marlon D M Santos1, Diogo B Lima2, Juliana S G Fischer1

  • 1Laboratory for Structural and Computational Proteomics, Carlos Chagas Institute, Fiocruz Paraná, Curitiba, Brazil.

Nature Protocols
|April 12, 2022
PubMed
Summary
This summary is machine-generated.

PatternLab V (PLV) is a powerful, updated computational tool for analyzing shotgun proteomic data. This software enhances protein identification and quantitation, improving user experience for complex biological samples.

More Related Videos

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
14:51

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Published on: November 13, 2021

5.5K
Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot
10:12

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Published on: October 28, 2021

3.9K

Related Experiment Videos

Last Updated: Jun 18, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

12.1K
Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
14:51

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Published on: November 13, 2021

5.5K
Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot
10:12

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Published on: October 28, 2021

3.9K

Area of Science:

  • Proteomics
  • Computational Biology
  • Bioinformatics

Background:

  • Shotgun proteomics identifies and quantifies proteins in complex biological samples.
  • Mass spectrometry generates vast datasets requiring specialized computational analysis.
  • Existing tools may lack comprehensive features for modern proteomic workflows.

Purpose of the Study:

  • To introduce PatternLab V (PLV), a significantly updated computational environment for shotgun proteomic data analysis.
  • To enhance protein identification, quantitation, and user experience in proteomic data analysis.
  • To provide a versatile tool for diverse experimental setups, including unsequenced organisms and time-course studies.

Main Methods:

  • Development and optimization of PatternLab V software modules.
  • Implementation of improved algorithms for protein identification and quantitation.
  • Update of the graphical user interface for enhanced usability.

Main Results:

  • PLV offers optimized modules for database preparation, protein identification, and statistical filtering.
  • Significant improvements in the number of protein identifications and speed of ion chromatogram extraction.
  • The PepExplorer module enables identification of de novo sequenced peptides.
  • PLV supports both labeled and label-free quantitation with in-depth result browsing.

Conclusions:

  • PatternLab V is a comprehensive and user-friendly computational environment for shotgun proteomics.
  • The updated software addresses key community needs, improving efficiency and scope of proteomic data analysis.
  • PLV is broadly applicable, interfaces with other software, and is freely available.