KEGG Metabolic Reaction Network (Undirected)

Donated on 11/27/2011

KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented.

Dataset Characteristics

Multivariate, Univariate, Text

Subject Area

Biology

Associated Tasks

Classification, Regression, Clustering

Feature Type

Integer, Real

# Instances

65554

# Features

-

Dataset Information

Additional Information

KEGG Metabolic pathways can be realized into network. Two kinds of network / graph can be formed. These include Reaction Network and Relation Network. In Reaction network, Substrate or Product compound are considered as Node and genes are treated as edge. Whereas in the relation network, Substrate and Product componds are considered as Edges while enzyme and genes are placed as nodes. We tool large number of metabolic pathways from KEGG XML. They were modeled into the graph as described above. With the help of Cytoscape tool, variety of network features were compunted.

Has Missing Values?

Yes

Introductory Paper

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

By P. Shannon, Andrew Markiel, Owen Ozier, N. Baliga, Jonathan T. Wang, D. Ramage, Nada Amin, B. Schwikowski, T. Ideker. 2003

Published in Genome Research

Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
no
no
no
no
no
no
no
no
no
no

0 to 10 of 29

Additional Variable Information

a) Pathway text b) Connected Components Integer (min:1, max:39 ) c) Diameter Integer (min:1, max:46 ) d) Radius Integer (min:1, max:13 ) e) Centralization Integer (min:0, max:1 ) f) Shortest Path Integer (min:2, max:23420 ) g) Characteristic Path Length Integer (min:1, max:15.9729 ) h) Avg.num.Neighbours real (min:0.67, max:3.44) i) Density real (min:0.0082, max:1) j) Heterogeneity real (min:0, max:1.796) k) Isolated Nodes Integer (min:0, max:3) l) Number of Self Loops Integer (min:0, max:4) m) Multi-edge Node Pair Integer (min:0, max:220) n) NeighborhoodConnectivity real (min:0.67, max:15.604) o) NumberOfDirectedEdges real (min:0.67, max:10.22) p) Stress real (min:0, max:2112.05) q) SelfLoops real (min:0, max:0.67) r) Partner Of MultiEdged NodePairs Integer (min:0, max:3) s) Degree real (min:1, max:10.22) t) TopologicalCoefficient real (min:0, max:1) u) BetweennessCentrality real (min:0, max:0.333) v) Radiality real (min:0.5437, max:30744573457 ) w) Eccentricity real (min:0.67, max:25.034) x) NumberOfUndirectedEdges real (min:0, max:0.67) y) ClosenessCentrality real (min:0.1022, max:1) z) AverageShortestPathLength real (min:0.67, max:12.67 ) aa) ClusteringCoefficient real (min:0, max:1) bb) nodeCount Integer (min:2, max:232) cc) edgeCount Integer (min:1, max:444)

Reviews

There are no reviews for this dataset yet.

Login to Write a Review
Download
1 citations
2703 views

Creators

Muhammad Naeem

Sohail Asghar

License

By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used by the UCI Machine Learning Repository.

Read Policy