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A biological network is a method of representing systems as complex sets of binary interactions or relations between various biological entities. [1] In general, networks or graphs are used to capture relationships between entities or objects. [1]
Biological network inference is the process of making inferences and predictions about biological networks. [1] By using these networks to analyze patterns in biological systems, such as food-webs, we can visualize the nature and strength of these interactions between species, DNA, proteins, and more.
Biological networks originate from evolution and therefore have less standardized components and potentially more complex interactions than networks designed by humans, such as electrical networks. At the cellular level, components of a network can include a large variety of proteins, many of which differ between organisms.
Weighted networks and correlation networks can often be approximated by "factorizable" networks. [4] [7] Such approximations are often difficult to achieve for sparse, unweighted networks. Therefore, weighted (correlation) networks allow for a parsimonious parametrization (in terms of modules and module membership) (chapters 2, 6 in [1]) and. [8]
An ecological network is a representation of the biotic interactions in an ecosystem, in which species (nodes) are connected by pairwise interactions (links).
The concept of gene co-expression networks was first introduced by Butte and Kohane in 1999 as relevance networks. [6] They gathered the measurement data of medical laboratory tests (e.g. hemoglobin level ) for a number of patients and they calculated the Pearson correlation between the results for each pair of tests and the pairs of tests which showed a correlation higher than a certain level ...
A general definition that subsumes the other definitions is that a value network is a network of roles linked by interactions in which economic entities engage in both tangible and intangible exchanges to achieve economic or social good.
Value network analysis (VNA) is a methodology for understanding, using, visualizing, optimizing internal and external value networks and complex economic ecosystems. [ 1 ] [ 2 ] The methods include visualizing sets of relationships from a dynamic whole systems perspective.