YaleGerstein Lab

Analysis of essentiality within protein networks

Haiyuan Yu, Dov Greenbaum, Hao Xin Lu, Xiaowei Zhu and Mark Gerstein

Abstract We introduce the notion here of 'marginal essentiality' through quantitatively combining the results from various phenotypic experiments. We connect this to protein interaction networks and find that it relates to many of their topological characteristics. In particular, network hubs (i.e., proteins with many interactions) tend to have a greater degree of marginal essentiality. We extend the network analysis to encompass directed networks (e.g., transcriptional regulatory networks). While transcription factors with many targets tend to be essential genes, surprisingly we find that hubs in the target population (e.g., genes regulated by many transcription factors), tend not to be essential.(Full Text)

Supplementary document: contains the supplementary tables and all supllementary metarials that the manuscript refers to.

Supplementary Data
       A. Yeast interaction network
 1. Y2H dataset by Ito et al
 2. Y2H dataset by Uetz et al
 3. in vivo pull-down dataset by Gavin et al
 4. in vivo pull-down dataset by Ho et al
 5. Manual collections in MIPS, BIND and DIP
 6. High-quality interaction network used in the revision
       B. Yeast regulatory network
 1. ChIp-chip dataset by Lee et al
 2. ChIp-chip dataset by Horak et al
 3. Dataset collected by Guelzim et al
 4. Dataset collected by the Transfac database

Last modified on Feb 15th, 2004