Human proteins (Vidal)
This network represens an initial version of a proteomescale map of Human
binary protein–protein interactions
Metadata
Statistics
Size  n =  3,133

Volume  m =  6,726

Loop count  l =  577

Wedge count  s =  88,809

Claw count  z =  1,399,841

Cross count  x =  27,308,384

Triangle count  t =  1,047

Square count  q =  10,216

4Tour count  T_{4} =  449,262

Maximum degree  d_{max} =  129

Average degree  d =  4.293 65

Fill  p =  0.001 370 02

Size of LCC  N =  2,783

Diameter  δ =  13

50Percentile effective diameter  δ_{0.5} =  4.264 35

90Percentile effective diameter  δ_{0.9} =  5.872 22

Median distance  δ_{M} =  5

Mean distance  δ_{m} =  4.803 13

Gini coefficient  G =  0.540 534

Balanced inequality ratio  P =  0.294 826

Relative edge distribution entropy  H_{er} =  0.926 225

Power law exponent  γ =  2.114 32

Tail power law exponent  γ_{t} =  3.031 00

Tail power law exponent with p  γ_{3} =  3.031 00

pvalue  p =  0.882 000

Degree assortativity  ρ =  −0.125 658

Degree assortativity pvalue  p_{ρ} =  1.817 28 × 10^{−44}

Clustering coefficient  c =  0.035 368 0

Spectral norm  α =  16.614 4

Algebraic connectivity  a =  0.069 808 5

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.229 05

Nonbipartivity  b_{A} =  0.186 364

Normalized nonbipartivity  b_{N} =  0.060 887 7

Algebraic nonbipartivity  χ =  0.107 163

Spectral bipartite frustration  b_{K} =  0.005 790 50

Controllability  C =  820

Relative controllability  C_{r} =  0.261 730

Plots
Matrix decompositions plots
Downloads
References
[1]

Jérôme Kunegis.
KONECT – The Koblenz Network Collection.
In Proc. Int. Conf. on World Wide Web Companion, pages
1343–1350, 2013.
[ http ]

[2]

JeanFrançois Rual, Kavitha Venkatesan, Tong Hao, Tomoko HirozaneKishikawa,
Amélie Dricot, Ning Li, Gabriel F. Berriz, Francis D. Gibbons, Matija Dreze,
and Nono AyiviGuedehoussou.
Towards a proteomescale map of the human protein–protein
interaction network.
Nature, (7062):1173–1178, 2005.
