Search results for "Network clustering"
showing 4 items of 4 documents
Algorithms for Graph and Network Analysis: Clustering and Search of Motifs in Graphs
2019
In this article we deal with problems that involve the analysis of topology in graphs modeling biological networks. In particular, we consider two important problems: (i) Network clustering, aiming at finding compact subgraphs inside the input graph in order to isolate molecular complexes, and (ii) searching for motifs, i.e., sub-structures repeated in the input network and presenting high significance (e.g., in terms of their frequency). We provide a compact overview of the main techniques proposed in the literature to solve these problems.
Synergistic effects and the co-existence of networks in clusters
2016
AbstractNetwork systems like clusters are characterized by the coexistence of relational architectures with ties and nodes of different nature. While recent research has analysed how a set of structural features shape the dynamics and effects of one cluster network, the outstanding question is to what extent such features and outcomes are influenced by the concomitance of distinct content-related linkages. This paper integrates both network and evolutionary economic geography perspectives to develop and test a model that links innovation performance with the benefits that stem from technical and business relations. Data collected in a biotech cluster in the Valencia region (Spain) demonstra…
Problems and Techniques
2017
When biological networks are considered, the extraction of interesting knowledge often involves subgraphs isomorphism check that is known to be NP-complete. For this reason, many approaches try to simplify the problem under consideration by considering structures simpler than graphs, such as trees or paths. Furthermore, the number of existing approximate techniques is notably greater than the number of exact methods. In this chapter, we provide an overview of three important problems defined on biological networks: network alignment, network clustering, and motifs extraction from biological networks. For each of these problems, we also describe some of the most important techniques proposed…
Restricted Neighborhood Search Clustering Revisited: An Evolutionary Computation Perspective
2013
Protein-protein interaction networks have been broadly studied in the last few years, in order to understand the behavior of proteins inside the cell. Proteins interacting with each other often share common biological functions or they participate in the same biological process. Thus, discovering protein complexes made of groups of proteins strictly related, can be useful to predict protein functions. Clustering techniques have been widely employed to detect significative biological complexes. In this paper, we integrate one of the most popular network clustering techniques, namely the Restricted Neighborhood Search Clustering (RNSC), with evolutionary computation. The two cost functions in…