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Bioinformatics

Visual Exploration of Biological Data

Current access to the biological databases is commonly done through the web. Usually, the different search interfaces present results as lists of entities that correspond to a search query, with links to both the entry and entries in related databases. In this work we offer a visual approach to navigate subsets of the searched data. Exploiting the network-structure of data resources, we can search, retrieve and visualize multiple data related to a given query. We will present different case studies that show the feasibility and advantages of this approach.
The vast quantity of biomedical data available presents two inmportant challenges, those of integration and interface design. In these work, we will focus on one of the most important and largest collections of biomedical data freely available on the internet, that of the European Bioinformatics Institute (EBI). The EBI maintains over 200 public databases containing biomedical information of various types, such as published medical documents (Medline), genomes (EnsEMBL), proteins (Uniprot), and DNA sequence information (Embl-Bank). To organize this data in a way useful for knowledge exploration, the EBI has endeavored to stay at the forefront of technological advance, providing new and increasingly sophisticated resources to meet the needs of its users. Different systems have been developed as a solution to the data integration challenge, for example, SRS, BioMart and the EB-Eye. Using any of these systems, multiple databases can be abstracted as a massive entity-relation graph. In this graph, individual knowledge points, such as documents, genes, proteins, and other object types correspond to nodes of the graph. Associations between database objects can then be modeled as links in the graph, connecting related nodes. Even though the EBI databases form an implicit entity-relation graph, the EBI’s current web interfaces offer no option to explore multiple areas of the graph simultaneously. Researchers explore the EBI databases by retrieving a single page of information at a time, essentially limiting them to viewing a single node at a time. They must continuously click forward and backward to retrieve additional information from other EBI databases. However, we believe that explicitly viewing and exploring multiple nodes in parallel will lead to improved performance in exploration and discovery tasks. Exploiting the network-structure of data resources, we can enable this exploration by starting with a query based subset of nodes from the EBI databases, and dynamically exploring and expanding links with other database entries, in order of query relevance or user preference. We can then visualize the data retrieved using network visualization tools based on either a simple force-directed layout algorithm or a more advanced schema following the concept of semantic substrates.

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2 comments for “Visual Exploration of Biological Data”

  1. [...] Visual Exploration of Biological Data // Bioinformatics :: Biology …In these work, we will focus on one of the most important and largest collections of biomedical data freely available on the internet, that of the European Bioinformatics Institute (EBI). The EBI maintains over 200 public databases … [...]

    Posted by Bioinformatics » Gut check reveals vast multicultural community of bugs in bowels | November 27, 2008, 11:08 pm
  2. [...] Visual Exploration of Biological Data // Bioinformatics :: Biology …In these work, we will focus on one of the most important and largest collections of biomedical data freely available on the internet, that of the European Bioinformatics Institute (EBI). The EBI maintains over 200 public databases … [...]

    Posted by Bioinformatics » Promises, Promises | November 30, 2008, 11:06 pm

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