Data integration and visualization system for enabling conceptual biology

Peddinti V. Gopalacharyulu (Corresponding Author), Erno Lindfors, Catherine Bounsaythip, Teemu Kivioja, Laxman Yetukuri, Jaakko Hollmén, Matej Orešič (Corresponding Author)

    Research output: Contribution to journalArticleScientificpeer-review

    18 Citations (Scopus)

    Abstract

    Motivation: Integration of heterogeneous data in life sciences is a growing and recognized challenge. The problem is not only to enable the study of such data within the context of a biological question but also more fundamentally, how to represent the available knowledge and make it accessible for mining.

    Results: Our integration approach is based on the premise that relationships between biological entities can be represented as a complex network. The context dependency is achieved by a judicious use of distance measures on these networks. The biological entities and the distances between them are mapped for the purpose of visualization into the lower dimensional space using the Sammon's mapping. The system implementation is based on a multi-tier architecture using a native XML database and a software tool for querying and visualizing complex biological networks. The functionality of our system is demonstrated with two examples: (1) A multiple pathway retrieval, in which, given a pathway name, the system finds all the relationships related to the query by checking available metabolic pathway, transcriptional, signaling, protein–protein interaction and ontology annotation resources and (2) A protein neighborhood search, in which given a protein name, the system finds all its connected entities within a specified depth. These two examples show that our system is able to conceptually traverse different databases to produce testable hypotheses and lead towards answers to complex biological questions.

    Original languageEnglish
    Pages (from-to)i177-i185
    JournalBioinformatics
    Volume21
    Issue numberSuppl. 1
    DOIs
    Publication statusPublished - 2005
    MoE publication typeA1 Journal article-refereed

    Keywords

    • xml

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