Centrality as a predictor of lethal proteins : performance and robustness

Zitieren

Dateien zu dieser Ressource

Prüfsumme: MD5:3fc5e0baadd9a9afebc7f1098cb1967d

BRANDES, Ulrik, David SCHOCH, 2014. Centrality as a predictor of lethal proteins : performance and robustness. In: FISCHBACH, Kai, ed. and others. MMB & DFT 2014 : Proceedings of the International Workshops ; Modeling, Analysis and Management of Social Networks and Their Applications (SOCNET 2014) & Demand Modeling and Quantitative Analysis of Future Generation Energy Networks and Energy-Efficient Systems (FGENET 2014). Bamberg:Univ. of Bamberg Press, pp. 11-18. ISBN 978-3-86309-208-5

@inproceedings{Brandes2014Centr-27807, title={Centrality as a predictor of lethal proteins : performance and robustness}, year={2014}, number={16}, isbn={978-3-86309-208-5}, address={Bamberg}, publisher={Univ. of Bamberg Press}, series={Schriften aus der Fakultät Wirtschaftsinformatik und Angewandte Informatik der Otto-Friedrich-Universität Bamberg}, booktitle={MMB & DFT 2014 : Proceedings of the International Workshops ; Modeling, Analysis and Management of Social Networks and Their Applications (SOCNET 2014) & Demand Modeling and Quantitative Analysis of Future Generation Energy Networks and Energy-Efficient Systems (FGENET 2014)}, pages={11--18}, editor={Fischbach, Kai}, author={Brandes, Ulrik and Schoch, David}, note={Link zur Originalveröffentlichung: http://nbn-resolving.de/urn:nbn:de:bvb:473-opus4-64867} }

deposit-license eng 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<br />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.<br /><br />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<br />by data. Centrality as a predictor of lethal proteins : performance and robustness 2014 2014-05-22T08:06:28Z Brandes, Ulrik MMB & DFT 2014 : Proceedings of the International Workshops ; Modeling, Analysis and Management of Social Networks and Their Applications (SOCNET 2014) & Demand Modeling and Quantitative Analysis of Future Generation Energy Networks and Energy-Efficient Systems (FGENET 2014) / Fischbach, Kai ... (eds.). - Bamberg : Univ. of Bamberg Press, 2014. - S. 11-18. - (Schriften aus der Fakultät Wirtschaftsinformatik und Angewandte Informatik der Otto-Friedrich-Universität Bamberg ; 16). - ISBN 978-3-86309-208-5 Brandes, Ulrik 2014-05-22T08:06:28Z Schoch, David Schoch, David

Dateiabrufe seit 01.10.2014 (Informationen über die Zugriffsstatistik)

Brandes_278071.pdf 256

Das Dokument erscheint in:

KOPS Suche


Stöbern

Mein Benutzerkonto