collins_yeast — Collins yeast interactome (2007)

Description

A network of physical protein–protein interactions in the budding yeast Saccharomyces cerevisiae, from the study of S. R. Collins and collaborators. The authors re-analyzed the two large-scale data sets of protein complexes identified by tandem affinity purification followed by mass spectrometry (AP/MS) of Gavin et al. (2006) and Krogan et al. (2006), and combined them with a purification enrichment (PE) scoring system calibrated against a reference set of known protein complexes. Nodes are proteins, and an undirected edge connects two proteins that were found to be co-complex associated (i.e. members of the same complex) in the high-confidence set of interactions. The node property name holds the systematic (ORF) name of the protein (e.g. YAL001C); the network has no edge properties.

This network comes from the yeast download page of the CCSB Interactome Database (Center for Cancer Systems Biology, Dana-Farber Cancer Institute), whose other data sets are in the entries yeast_interactome_ccsb (the yeast binary Y2H maps CCSB-YI1, Ito core and Uetz screen, and literature-curated and gold-standard reference sets), interactome_vidal (the first human binary map CCSB-HI1/HI-I-05), human_interactome_2014 (the human maps HI-II-14 and Lit-BM-13) and celegans_interactomes (the C. elegans interactome networks).

Tags

Biological Protein interactions Unweighted

Citation

S.R. Collins et al., "Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae." Mol. Cell. Proteomics 6(3), 439-450 (2007) 10.1074/mcp.m600381-mcp200 Sci-Hub

Upstream URL OK

https://web.archive.org/web/20200205030615/http://interactome.dfci.harvard.edu/S_cerevisiae/index.php?page=download

Networks

Tip: hover over a column header for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
collins_yeast	1,622	9,070	11.18	16.23	58.74	630.48	0.61	0.62	15	0.62	Undirected	Unipartite			33 KiB	58 KiB	55 KiB	46 KiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.