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myocardial_inflamome — Myocardial infarction inflammation protein interactions (2011)

Description

Network of human protein-protein interactions (PPIs) related to inflammation and prognosis after myocardial infarction (MI), called "My-Inflamome", from F. J. Azuaje and collaborators. Nodes are human proteins (identified by gene symbols), and an undirected edge indicates an experimentally validated physical interaction between two proteins in humans. The network was built from a set of 415 seed proteins: 28 well-known biomarkers of inflammation and prognosis after MI (e.g. TNF, IL6, CRP, FAS), expanded with genes that are functionally and phenotypically similar to them according to a gene prioritization. All the human PPIs of the seed proteins were retrieved from the DIP, IntAct and MINT databases (c. 2010), and their union forms the network. The data contain the largest connected component of the network (reported as 2,532 proteins and 6,131 interactions; the file contains 2,531 distinct protein names, and a few self-interactions), on which the analyses of the paper are based.

The nodes have the following properties:

  • name: the protein (gene symbol, or a database identifier when no symbol was assigned).
  • is_seed: whether the protein is one of the seeds; is_biomarker: whether it is one of the known biomarkers (seeds not in the largest component are not included).
  • module: the module of the protein (1 to 21), found by the authors with a greedy modularity-maximization clustering (PolarMapper); submodule: its submodule, numbered across all modules; traffic: the "traffic" (betweenness centrality) of the protein, as computed by the authors. These are -1 (or NaN) for the proteins not listed in the module tables.1

  1. Description obtained in part from the ICON project. ↩

Tags
Biological Protein interactions Unweighted Metadata
Citation
  • F. J. Azuaje, S. Rodius, L. Zhang, Y. Devaux, D. R. Wagner, "Information encoded in a network of inflammation proteins predicts clinical outcome after myocardial infarction." BMC Medical Genomics 4, 59 (2011) 10.1186/1755-8794-4-59 Sci-Hub
Upstream URL OK
https://doi.org/10.1186/1755-8794-4-59
Upstream license
Creative Commons Attribution 2.0 Generic (CC BY 2.0), https://creativecommons.org/licenses/by/2.0/
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
myocardial_inflamome 2,531 6,131 4.84 17.55 28.24 24.11 -0.33 0.02 10 1.00 Undirected Unipartite name is_seed is_biomarker module submodule traffic 29 KiB 45 KiB 45 KiB 41 KiB