Formal Concept Analysis and Knowledge Integration for Highlighting Statistically Enriched Functions from Microarrays Data

نویسنده

  • Sidahmed Benabderrahmane
چکیده

In this paper we introduce a new method for extracting enriched biological functions from transcriptomic databases using an integrative bi-classification approach. The initial gene datasets are firstly represented as a formal context (objects × attributes), where objects are genes, and attributes are their expression profiles and complementary informations of different knowledge bases. After that, Formal Concept Analysis (FCA) is applied for extracting formal concepts regrouping genes having similar transcriptomic profiles and functional behaviors. An enrichment analysis is then performed in order to identify the pertinent formal concepts from the generated Galois lattice, and to extract biological functions that could participate in the proliferation of cancers.

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تاریخ انتشار 2014