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

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.1K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.1K
Proteomics01:33

Proteomics

7.4K
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...
7.4K

You might also read

Related Articles

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

Sort by
Same author

c-JUN controls microbial colonization via selective phagocytosis in the sea anemone Nematostella.

Nature communications·2026
Same author

The Role of Meprins on the Brain Extracellular Matrix and Perineuronal Nets.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2026
Same author

Interacting Species Database (ISDB): comprehensive resource for interspecies interactions at the molecular level.

Bioinformatics (Oxford, England)·2026
Same author

Meet NUM-ENRICH: A Collaborative National Effort to Extend and Harmonize Research Infrastructures Within the German Network University Medicine.

Studies in health technology and informatics·2026
Same author

Enabling Privacy-Preserving Federated Learning in Healthcare: The FLAME Architecture and Policy Framework.

Studies in health technology and informatics·2026
Same author

A Maturity Model for the Enforcement of PETs in Federated Settings.

Studies in health technology and informatics·2026

Related Experiment Video

Updated: Jul 10, 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

Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top-down proteomics.

Kyowon Jeong1,2, Philipp T Kaulich3, Wonhyeuk Jung4

  • 1Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen, Germany.

Proteomics
|November 24, 2023
PubMed
Summary
This summary is machine-generated.

Top-down proteomics (TDP) data analysis is hindered by inaccurate false discovery rate (FDR) estimation. We show that target-decoy approach (TDA) FDR in TDP is flawed due to precursor mass errors, proposing a correction formula.

Keywords:
FDRdeconvolutionfalse discovery rateprecursortop-down proteomics

More Related Videos

Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry
10:05

Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry

Published on: October 24, 2018

9.5K
Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

17.1K

Related Experiment Videos

Last Updated: Jul 10, 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
Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry
10:05

Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry

Published on: October 24, 2018

9.5K
Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

17.1K

Area of Science:

  • Proteomics
  • Biochemistry
  • Analytical Chemistry

Background:

  • Top-down proteomics (TDP) offers comprehensive proteoform analysis, surpassing bottom-up proteomics (BUP).
  • Accurate data analysis, particularly false discovery rate (FDR) estimation, remains a significant challenge in TDP.
  • The target-decoy approach (TDA) is widely used for FDR estimation but was developed for BUP.

Purpose of the Study:

  • To evaluate the accuracy of TDA-based FDR estimation at the proteoform level in TDP.
  • To identify factors contributing to potential inaccuracies in TDA-based FDR estimation for TDP.
  • To propose a method for correcting proteoform-level FDR bias in TDP.

Main Methods:

  • Analysis of TDP data, focusing on precursor mass deconvolution.
  • Comparison of TDA-based FDR with actual proteoform identification rates.
  • Development of a modified FDR calculation incorporating precursor deconvolution error rates.

Main Results:

  • Evidence suggests TDA-based FDR estimation is inaccurate for proteoform identification in TDP.
  • Erroneous deconvolution of precursor masses is identified as a key factor causing FDR bias.
  • The proposed formula combining TDA-FDR and precursor deconvolution error rate corrects for this bias.

Conclusions:

  • Conventional TDA-based FDR in TDP may represent protein-level, not proteoform-level, FDR.
  • Accounting for precursor deconvolution errors is crucial for accurate proteoform identification.
  • The developed correction formula enhances the reliability of TDP data analysis.