Autor(es):
Noronha, Alberto Miguel Silva de
Data: 2013
Identificador Persistente: http://hdl.handle.net/1822/28081
Origem: RepositóriUM - Universidade do Minho
Descrição
Dissertação de mestrado em Bioinformática The recent sequencing techniques and omics approaches are generating huge amounts of data that can provide ways to extract meaningful knowledge, by resorting to appropriate computational tools. One important technique resorts to the use of genome scale model reconstructions. These models are widely used in Metabolic Engineering, attempting to optimize an organism's functions, genetically modifying it to produce compounds of industrial interest.
Another area that became widely important within the fields of Systems Biology and Bioinformatics was network analysis and visualization. Networks can provide a way to better understand the relationships between biological entities, by allowing their visual representation. However, biological networks usually comprise a large number of entities and interactions, that cannot be easily interpreted by the human eye.
Integrating visualization and analysis is, therefore, a goal of high interest in several scientific areas, and this has been tackled by several visualization tools available. However, regarding the integration of metabolic engineering techniques with metabolic network visualization, there are still few examples of success. Usually, it is necessary to use more than one tool and the agility of the methods is limited.
In this work, a metabolic network visualization framework is presented, with the goal of being a tool that will help researchers in metabolic engineering projects. This framework is divided in two layers: the first deals with the importation and exportation of networks in different formats, while the other layer provides all the visualization and edition features.
A metabolic layout is based on the reactions contained in the metabolic model, and it can represent just a part of the metabolism of an organism. To have the possibility to use the same layout in different models, a strategy was defined to map the entities of the visualization with the entities of the model.
The layouts are displayed in a bipartite graph, with different node types and colors. It is possible to visualize additional information of the network by clicking the nodes. Some of the features include dragging, zooming and highlighting. On top of all this, it is also possible to apply filters and overlap information over these networks. The filters can change what is visible in the network, while the overlaps allow defining new labels, colors and shapes to the nodes, and new colors and thickness to the edges. Finally, the framework was also integrated within OptFlux, an open-source software to support metabolic engineering available at www.optflux.org, to provide a connection between visualization and metabolic simulation methods.