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 Experiment Videos

DBDigger: reorganized proteomic database identification that improves flexibility and speed.

David L Tabb1, Chandrasegaran Narasimhan, Michael Brad Strader

  • 1Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6164, USA. tabbdl@ornl.gov

Analytical Chemistry
|April 15, 2005
PubMed
Summary

DBDigger is a new algorithm that accelerates proteomic database searches by reorganizing how candidate sequences and spectra are compared. This method significantly speeds up analysis and improves handling of posttranslational modifications (PTMs).

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

A novel <i>Schinkia</i> sp. respires nitrous oxide over a broad pH range.

Applied and environmental microbiology·2026
Same author

Detection and characterization of protein methylation in bacteriophages and their host, <i>Cellulophaga baltica</i>, during infection.

mSystems·2026
Same author

Capacity of Arctic fjord sediments to degrade carbohydrates from permafrost active layer.

Microbiology spectrum·2026
Same author

High-resolution multi-omics enhances prediction and detection of smORF-encoded proteins in the human gut microbiome.

Nature communications·2026
Same author

Seasonal thawing of high Arctic soils triggers selective microbial growth and predation.

mSystems·2026
Same author

Bacteria covalently incorporate polyfluoroalkyl carboxylates into membrane lipids.

Nature microbiology·2026

Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Database search algorithms like Sequest and Mascot are crucial for analyzing proteomic tandem mass spectrometry data.
  • Current algorithms face bottlenecks in comparing candidate sequences to spectra, limiting efficiency.
  • Posttranslational modification (PTM) searching often introduces significant performance degradation.

Purpose of the Study:

  • Introduce DBDigger, a novel algorithm designed to optimize the proteomic database search process.
  • Address the computational bottlenecks in current identification algorithms.
  • Enhance the efficiency and flexibility of PTM searching in proteomics.

Main Methods:

  • Reorganize the database search by comparing spectra to candidate sequences, rather than vice versa.

Related Experiment Videos

  • Generate candidate sequences once per HPLC separation, reducing redundant predictions.
  • Implement context-dependent PTM searching to limit modifications to specific sequence contexts.

    • Main Results:

    • Achieve acceleration of proteomic database searches by over an order of magnitude.
    • Significantly reduce the performance penalty associated with PTM searching.
    • Demonstrate the effectiveness of DBDigger with MASPIC, a new statistical scorer.

    Conclusions:

    • DBDigger offers a substantial improvement in speed and efficiency for proteomic database searches.
    • The context-dependent PTM searching feature enhances flexibility and reduces computational overhead.
    • This algorithm provides a powerful tool for rapid and flexible proteomic data analysis.