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

6.6K
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...
6.6K
Proteomics01:33

Proteomics

7.5K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.5K
Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

5.5K
Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass.  One common type of ionization, known as electrospray ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave...
5.5K

You might also read

Related Articles

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

Sort by
Same authorSame journal

Instrument-Software Synergy in Proteomics: Systematic Evaluation across Mass Spectrometry Platforms, Search Engines, and Rescoring Methods.

Journal of proteome research·2026
Same authorSame journal

Analysis and Annotation of c-Type Ions in Peptide Mass Spectral Libraries.

Journal of proteome research·2026
Same author

Integration of alternative fragmentation techniques into standard LC-MS workflows using a single deep learning model enhances proteome coverage.

Nature methods·2026
Same author

Unusual Fragmentations of Silylated Polyfluoroalkyl Compounds Induced by Electron Ionization.

Journal of the American Society for Mass Spectrometry·2025
Same author

Prosit-XL: enhanced cross-linked peptide identification by fragment intensity prediction to study protein interactions and structures.

Nature communications·2025
Same author

Integrating Alternative Fragmentation Techniques into Standard LC-MS Workflows Using a Single Deep Learning Model Enhances Proteome Coverage.

bioRxiv : the preprint server for biology·2025

Related Experiment Video

Updated: Jul 29, 2025

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

12.0K

AIomics: Exploring More of the Proteome Using Mass Spectral Libraries Extended by Artificial Intelligence.

Lewis Y Geer1, Joel Lapin1,2, Douglas J Slotta1

  • 1Mass Spectrometry Data Center, National Institute of Standards and Technology, Biomolecular Measurement Division, 100 Bureau Dr., Gaithersburg, Maryland 20899, United States.

Journal of Proteome Research
|May 26, 2023
PubMed
Summary

Predicting peptide spectra using neural networks improves proteomic identification. This approach enhances accuracy by 82% and increases peptide identifications by 8%, aiding in the discovery of modified and nonspecifically cleaved peptides.

Keywords:
algorithmsmachine learningpeptidesproteome analysissearch engine methodstandem mass spectrometry

More Related Videos

Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry
11:54

Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry

Published on: March 23, 2020

9.6K
Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
09:35

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

Published on: April 1, 2017

13.9K

Related Experiment Videos

Last Updated: Jul 29, 2025

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

12.0K
Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry
11:54

Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry

Published on: March 23, 2020

9.6K
Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
09:35

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

Published on: April 1, 2017

13.9K

Area of Science:

  • Proteomics
  • Computational Biology
  • Biochemistry

Background:

  • Identifying peptides in complex biological samples is challenging due to molecular permutations.
  • Current sequence search algorithms for peptide identification can lead to false positives/negatives.
  • Spectral library searching offers high sensitivity and specificity but is difficult to scale proteome-wide.

Purpose of the Study:

  • To develop a method for creating comprehensive spectral libraries for improved peptide identification.
  • To leverage neural networks for predicting complete peptide spectra.
  • To enhance the accuracy and scope of proteomic analyses.

Main Methods:

  • Utilized neural networks to predict complete peptide spectra, including modified peptides.
  • Generated predicted spectral libraries to replace simplified spectra from sequence records.
  • Applied these predicted libraries to rescore matches from large-scale sequence searches.

Main Results:

  • Rescoring significantly improved the separation of true and false peptide identifications by 82%.
  • Achieved an overall 8% increase in peptide identifications.
  • Observed a 21% increase in nonspecifically cleaved peptides and a 17% increase in phosphopeptides.

Conclusions:

  • Neural network-predicted spectral libraries offer a scalable solution for comprehensive proteomic analysis.
  • This method enhances the accuracy and yield of peptide identification, particularly for modified and atypical peptides.
  • The approach advances the identification of complex biological molecules in biosamples.