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

Motif-based protein ranking by network propagation.

Rui Kuang1, Jason Weston, William Stafford Noble

  • 1Department of Computer Science, Columbia University New York, NY 10027, USA.

Bioinformatics (Oxford, England)
|August 4, 2005
PubMed
Summary

MotifProp, a new graph-based algorithm, enhances remote homology detection by analyzing protein-motif networks. It improves upon existing methods like PSI-BLAST for identifying subtle evolutionary relationships.

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

Long-term Survival Rates in U.S. Veterans Shunted for iNPH: A Focused Analysis of Radiological Predictors.

World neurosurgery·2026
Same author

Author Correction: Ontogeny and transcriptional regulation of Thetis cells.

Nature·2026
Same author

drGT: Interpretable Drug Response Prediction with Attention-Guided Gene Attribution on a Drug-Cell-Gene Heterogeneous Graph.

BMC bioinformatics·2026
Same author

Prioritizing peptides for targeted mass spectrometry experiments using deep learning.

bioRxiv : the preprint server for biology·2026
Same author

Embryo-scale Visual Cell Sorting reveals a conserved transcriptomic signature of nucleolar size linked to proteostasis.

bioRxiv : the preprint server for biology·2026
Same author

Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC.

Nature communications·2026

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Sequence similarity is crucial for inferring protein structure and function.
  • Existing homology detection tools (e.g., BLAST, PSI-BLAST) struggle with remote targets.
  • Detecting subtle evolutionary relationships remains a challenge in bioinformatics.

Purpose of the Study:

  • To introduce MotifProp, a novel graph-based propagation algorithm.
  • To improve the detection of subtle similarity relationships in protein sequences.
  • To enhance homology detection beyond traditional pairwise comparison methods.

Main Methods:

  • Developed a general graph-based propagation algorithm named MotifProp.
  • Constructed a protein-motif network where proteins connect to their k-mer based motif features.

Related Experiment Videos

  • Utilized PSI-BLAST for initial ranking to bootstrap the propagation process.

    • Main Results:

    • MotifProp significantly improves ranking results compared to baseline algorithms like PSI-BLAST.
    • The algorithm effectively identifies more subtle similarity relationships.
    • Top-ranked motifs and motif-rich regions provide interpretable insights into conserved structural components.

    Conclusions:

    • MotifProp offers a powerful new approach for detecting remote homologies.
    • The motif-based propagation method enhances the sensitivity of homology detection.
    • Interpretability of results aids in understanding conserved protein structures and functions.