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

Using indirect protein-protein interactions for protein complex predication.

Hon Nian Chua1, Kang Ning, Wing-Kin Sung

  • 1Graduate School of Integrated Sciences, National University of Singapore, Singapore. g0306417@nus.edu.sg

Computational Systems Bioinformatics. Computational Systems Bioinformatics Conference
|October 24, 2007
PubMed
Summary
This summary is machine-generated.

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 pan-cancer single-cell atlas uncovers the role of sex hormones and chromosomes in sex-divergent reprogramming of the tumor microenvironment.

Cell communication and signaling : CCS·2026
Same author

Sulfated bile acid produced by a human gut commensal alleviates paediatric sepsis in mice.

Nature microbiology·2026
Same author

CRISPR Screening Reveals SAA1-Driven Neutrophil Extracellular Traps Promote CD8⁺ T Cell Dysfunction in Renal Cell Carcinoma.

Cancer research·2026
Same author

Global Soil Water Stable Isotope Dataset.

Scientific data·2026
Same author

Unraveling the colonization process of microeukaryotic communities on artificial micro-ecological islands.

Environmental microbiome·2026
Same author

Identification of Human Transferrin Receptor as an Entry Co-receptor for Parvovirus B19 Infection of Human Erythroid Progenitor Cells.

bioRxiv : the preprint server for biology·2026
Same journal

Novel Gene Discovery in the Human Malaria Parasite using Nucleosome Positioning Data.

Computational systems bioinformatics. Computational Systems Bioinformatics Conference·2014
Same journal

Proceedings of Computational Systems Bioinformatics 2008. August 26-29, 2008. Palo Alto, California, USA.

Computational systems bioinformatics. Computational Systems Bioinformatics Conference·2009
Same journal

Graph wavelet alignment kernels for drug virtual screening.

Computational systems bioinformatics. Computational Systems Bioinformatics Conference·2009
Same journal

Fast multisegment alignments for temporal expression profiles.

Computational systems bioinformatics. Computational Systems Bioinformatics Conference·2009
Same journal

Knowledge representation and data mining for biological imaging.

Computational systems bioinformatics. Computational Systems Bioinformatics Conference·2009
Same journal

Efficient haplotype inference from pedigrees with missing data using linear systems with disjoint-set data structures.

Computational systems bioinformatics. Computational Systems Bioinformatics Conference·2009
See all related articles

This study enhances protein complex prediction by incorporating indirect protein-protein interactions (PPIs) and a functional association weight (FS-Weight). This improves accuracy in identifying novel protein complexes from noisy PPI networks.

Area of Science:

  • Biochemistry
  • Computational Biology
  • Systems Biology

Background:

  • Protein complexes are crucial for cellular organization and function.
  • Predicting protein complexes from protein-protein interaction (PPI) networks is vital for biological discovery but challenging due to network noise.
  • Proteins without direct interactions can share functions through shared interaction partners (level-2 neighbors).

Purpose of the Study:

  • To investigate the utility of indirect interactions and topological weighting for improving protein complex prediction.
  • To develop and evaluate a novel algorithm for protein complex identification using modified PPI networks.

Main Methods:

  • Weighted protein-protein interaction (PPI) networks using functional association weight (FS-Weight).
  • Incorporation of high-weight indirect (level-2) interactions into the network.

Related Experiment Videos

  • Application of existing clustering algorithms and a novel clique-merging algorithm on the modified networks.

    • Main Results:

    • The integration of indirect interactions and topological weighting significantly enhances the precision of protein complex prediction algorithms.
    • The proposed novel algorithm demonstrates strong performance on the modified, augmented PPI networks.
    • The method effectively leverages only PPI network data for improved complex prediction.

    Conclusions:

    • Augmenting PPI networks with weighted indirect interactions improves protein complex prediction accuracy.
    • The novel algorithm offers a robust approach for identifying protein complexes, particularly novel ones.
    • This method provides a valuable tool for biological research using solely PPI network information.