RESUMO
Data from high-throughput experimental methods are currently being used to construct complex biological networks. These include regulatory gene networks, regulatory protein-DNA networks, protein-protein interaction networks, or metabolic networks. Independent of its type, every network can be characterized by a number of parameters such as number of nodes, number of edges connecting nodes, direction and weight of edges, in- and out-degree of nodes, etc. One can draw an analogy of such rather simple network parameters to the primary sequence of proteins or nucleic acids. More insight can be gained by an analysis of the secondary and tertiary structure of biomolecules, which often contain motifs. The same holds for biological networks. The occurrence and frequency of certain motifs or pattern characterize the topology and often the functional space of a network. Here, we describe the utilization of the free software MAVisto, which was designed to mine networks for typical motifs by combining a flexible motif search algorithm with interactive exploration methods and sophisticated visualization techniques.
Assuntos
Algoritmos , Redes Reguladoras de Genes/genética , Redes e Vias Metabólicas/genética , Mapas de Interação de Proteínas/genética , Software , Biologia de Sistemas/métodos , Gráficos por Computador , Mineração de Dados/métodos , Conceitos Matemáticos , Ferramenta de BuscaRESUMO
Centrality analysis has been shown to be a valuable method for the structural analysis of biological networks. It is used to identify key elements within networks and to rank network elements such that experiments can be tailored to interesting candidates. Several centrality measures have been studied, in particular for gene regulatory, metabolic and protein interaction networks. However, these centralities have been developed in other fields of science and are not adapted to biological networks. In particular, they ignore functional building blocks within biological networks and therefore do not consider specific network substructures of interest. We incorporate functional substructures (motifs) into network centrality analysis and present a new approach to rank vertices of networks. A method for motif-based centrality analysis is presented and two extensions are discussed which broaden the idea of motif-based centrality to specific functions of particular motif elements, and to the consideration of classes of related motifs. The presented method is applied to the gene regulatory network of Escherichia coli, where it yields interesting results about key regulators.
Assuntos
Redes Reguladoras de Genes/genética , Algoritmos , DNA Bacteriano/genética , Escherichia coli/genética , Regulação Bacteriana da Expressão Gênica/genética , Genes Bacterianos/genética , Genes Reguladores/genética , Redes e Vias Metabólicas , Modelos Genéticos , Transcrição Gênica/genéticaRESUMO
UNLABELLED: MAVisto is a tool for the exploration of motifs in biological networks. It provides a flexible motif search algorithm and different views for the analysis and visualization of network motifs. These views help to explore interesting motifs: the frequency of motif occurrences can be compared with randomized networks, a list of motifs along with information about structure and number of occurrences depending on the reuse of network elements shows potentially interesting motifs, a motif fingerprint reveals the overall distribution of motifs of a given size and the distribution of a particular motif in the network can be visualized using an advanced layout algorithm. AVAILABILITY: MAVisto is platform independent and available free of charge as a Java webstart application at http://mavisto.ipk-gatersleben.de/ CONTACT: schwoebb@ipk-gatersleben.de SUPPLEMENTARY INFORMATION: Can be found at http://mavisto.ipk-gatersleben.de/