Topological structure analysis of the protein-protein interaction network in budding yeast

Clicks: 1
ID: 306476
2003
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #1,179 of 1,214 articles by views in Nucleic Acids Research

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,214 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Interaction detection methods have led to the discovery of thousands of interactions between proteins, and discerning relevance within large-scale data sets is important to present-day biology. Here, a spectral method derived from graph theory was introduced to uncover hidden topological structures (i.e. quasi-cliques and quasi-bipartites) of complicated protein-protein interaction networks. Our analyses suggest that these hidden topological structures consist of biologically relevant functional groups. This result motivates a new method to predict the function of uncharacterized proteins based on the classification of known proteins within topological structures. Using this spectral analysis method, 48 quasi-cliques and six quasi-bipartites were isolated from a network involving 11,855 interactions among 2617 proteins in budding yeast, and 76 uncharacterized proteins were assigned functions.
Reference Key
openalex_W2121470019 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ding-fang Bu
Journal Nucleic Acids Research
Year 2003
DOI
10.1093/nar/gkg340
URL
https://academic.oup.com/nar/article-pdf/31/9/2443/3773904/gkg340.pdf
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.