A biological network is any network that applies to biological systems. A network is any system with sub-units that are linked into a whole, such as species units linked into a whole food web. Biological networks provide a mathematical analysis of connections found in ecological, evolutionary, and physiological studies, such as neural networks.[1]
Network biology and bioinformatics
Complex biological systems may be represented and analyzed as computable networks. For example, ecosystems can be modelled as networks of interacting species or individuals. Similarly, a protein can be modelled as a network of amino acids with nodes and edges. Amino acids can be represented as a network of atoms such as carbon, nitrogen and oxygen.
As early as the 1980s, researchers started viewing DNA or genomes as the dynamic storage of a language system with precise computable finite states represented as a finite state machine (Searls, 1993)[broken citation]. Recent complex systems research has also suggested some far-reaching commonality in the organization of information in problems from biology, computer science, and physics, such as the Bose–Einstein condensate (a special state of matter, Bianconi and A.L. Barabási, 2001[broken citation]).
Bioinformatics has increasingly shifted its focus from individual genes, proteins, and search algorithms to large-scale networks often denoted as -omes such as biome, interactome, genome and proteome. Such theoretical studies have revealed that biological networks share many features with other networks such as the Internet or social networks, e.g. their network topology.
Networks in biology
Protein-protein interaction networks
Main article: interactome
Many protein-protein interactions (PPIs) in a cell form protein interaction networks (PINs) where proteins are nodes and their interactions are edges. PINs are the most intensely analyzed networks in biology. There are dozens of PPI detection methods to identify such interactions. The yeast two-hybrid system is a commonly used experimental technique for the study of binary interactions.[2]
Gene regulatory networks (DNA-protein interaction networks)
Main article: Gene regulatory network
The activity of genes is regulated by transcription factors, proteins that typically bind to DNA. Most transcription factors bind to multiple binding sites in a genome. As a result, all cells have complex gene regulatory networks. For instance, the human genome encodes on the order of 1,400 DNA-binding transcription factors that regulate the expression of more than 20,000 human genes.[3] Technologies to study gene regulatory networks include ChIP-chip, ChIP-seq, CliP-seq, and others.
Metabolic networks
Main article: metabolic network
The chemical compounds of a living cell are connected by biochemical reactions which convert one compound into another. The reactions are catalyzed by enzymes. Thus, all compounds in a cell are parts of an intricate biochemical network of reactions which is called metabolic network.
Signaling networks
Main article: Cell signaling
Signals are transduced within cells or in between cells and thus form complex signaling networks. For instance, in the MAPK/ERK pathway is transduced from the cell surface to the cell nucleus by a series of protein-protein interactions, phosphorylation reactions, and other events. Signaling networks typically integrate protein-protein interaction networks, gene regulatory networks, and metabolic networks.
Neuronal network
Main article: Biological neural network
The network of connections between neurons (nerve cells) in the brain and the remainder of the nervous system.
Food webs
Main article: Food web
All organisms are connected to each other because they eat each other. That is, if a species eats or is eaten by another species they are connected in an intricate food web of bait and prey links.
See also
- Daftar/Tabel -- omics topics in biology
- Biological network inference
- Applied Statistics
- Biostatistics
- Computational Biology
- Systems biology
- Interactome
References
Books
- E. Estrada, "The Structure of Complex Networks: Theory and Applications", Oxford University Press, 2011, ISBN 978-0-199-59175-6
External links
