Synonyms
Biological pathways; Molecular interaction graphs; Protein-protein interaction networks; Signal transduction networks; Transcriptional networks
Definition
A biological network is a graph-structured representation of binarized interactions among biological objects. Typically, the nodes in such a graph represent biological molecules, and the edges are labeled to represent different forms of interactions between molecules.
Example: A transcriptional network is a directed graph where a node represents either a protein (a transcription factor) or a region of the chromosome such that the edges can be constructed from the protein node to the chromosomal region. The edge in the graph represents that the protein can initiate the transcription (production of messenger RNA) process.
Key Points
A biological network is typically a node and edge attributed graph, where the edges can have different semantics depending on the kind of network. In some networks, the edges may be weighted,...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Baitaluk M, Qian X, Godbole S, Raval A, Ray A, Gupta A. PathSys: integrating molecular interaction graphs for systems biology. BMC Bioinf. 2006;7(1):55.
Eckman BA, Brown PG. Graph data management for molecular and cell biology. IBM J Res Dev. 2006;50(6):545–60.
Leser U. A query language for biological networks. Bioinformatics. 2005;21(Suppl 2):ii33–9.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Gupta, A. (2018). Biological Networks. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1308
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1308
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering