Sets2Networks: network inference from repeated observations of sets.

ABSTRACT:

Background

The skeleton of complex systems can be represented as networks where vertices represent entities, and edges represent the relations between these entities. Often it is impossible, or expensive, to determine the network structure by experimental validation of the binary interactions between every vertex pair. It is usually more practical to infer the network from surrogate observations. Network inference is the process by which an underlying network of relations between entities is determined from indirect evidence. While many algorithms have been developed to infer networks from quantitative data, less attention has been paid to methods which infer networks from repeated co-occurrence of entities in related sets. This type of data is ubiquitous in the field of systems bi

SUBMITTER: Clark NR 

PROVIDER: S-EPMC3443648 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature