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

Sidahmed Benabderrahmane (1)

1 DREAM - Diagnosing, Recommending Actions and Modelling

In this paper we introduce a new method for extracting enriched biological functions from transcriptomic databases using an integrative bi-classication 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 information 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.

Mots clés: classification; data mining

Domaines: Apprentissage [cs.LG]

Sidahmed Benabderrahmane. Formal Concept Analysis and Knowledge Integration for Highlighting Statistically Enriched Functions from Microarrays Data. International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2014, Granada, Spain,, Apr 2014, Granada, Spain. pp.1. ⟨hal-00935378⟩