Centrality as a Predictor of Lethal Proteins: Performance and Robustness

David Schoch, Ulrik Brandes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Centrality-Lethality Hypothesis states that proteins with
a higher degree centrality are more likely to be lethal, i.e. proteins involved
in more interactions are more likely to cause death when knocked
off. This proposition gave rise to several new investigations in which
stronger associations were obtained for other centrality measures. Most
of this previous work focused on the well known protein-interaction network
of Saccharomyces cerevisiae. In a recent study, however, it was found
that degree and betweenness of lethal proteins is significantly above average
across 20 different protein-interaction networks. Closeness centrality,
on the other hand, did not perform as well.
We replicate this study and show that the reported results are due largely
to a misapplication of closeness to disconnected networks. A more suitable
variant actually turns out to be a better predictor than betweenness
and degree in most of the networks. Worse, we find that despite the different
theoretical explanations they offer, the performance ranking of
centrality indices varies across networks and depends on the somewhat
arbitrary derivation of binary network data from unreliable measurements.
Our results suggest that the celebrated hypothesis is not supported
by data.
Original languageEnglish
Title of host publicationProceedings of the International Workshops SOCNET 2014 and FGENET 2014
PublisherUniversity of Bamberg Press
Pages11-18
Number of pages8
Publication statusPublished - 2014

Keywords

  • network centrality
  • protein networks
  • centrality-lethality

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