Abstract | Such approaches build on the assumption that protein interaction networks can be viewed as maps in which diseases can be identified with localized perturbation within a certain neighborhood. |
Author Summary | To disentangle these complex interactions it is necessary to study genotype-phenotype relationships in the context of protein-protein interaction networks . |
Interaction patterns of disease proteins within the Interactome | In order to evaluate the extent to which such topological community detection algorithms can be used to predict disease modules, we chose three representative, methodologically distinct algorithms that have been successfully applied to identify communities of functionally related proteins (functional modules) in protein interaction networks : (i) A link community algorithm [14], which is based on link-similarities and can also capture hierarchical communities, (ii) the Louvain method, which maximizes a global modularity function [21], and (iii) the Markov Cluster Algorithm (MCL), which detects dense regions based on random flow [24]. |
Introduction | molecules or proteins) interact among each other, i.e., the structure of the underlying interaction network . |
Introduction | Other models, known as dynamic models, include the structure of the interaction network and also an equation for each component, which describes how the state of this component changes in time due to the influence of other cell components (e.g. |
Introduction | Since systems whose interaction networks and dynamics are known equally well are rare, current control strategies are based on either the network structure [7, 9, 10, 12, 13] or its dynamics (function) [11, 20—22]. |