Formal Concept Analysis Applied to Transcriptomic Data

Mehwish Alam (1) , Adrien Coulet (1) , Amedeo Napoli (1) , Malika Smaïl-Tabbone (1)

1 ORPAILLEUR - Knowledge representation, reasonning

Identifying functions shared by genes responsible for cancer is a challenging task. This paper describes the preparation work for applying Formal Concept Analysis (FCA) to complex biological data. We present here a preliminary experiment using these data on a core context with the addition of domain knowledge. The resulting concept lattices are explored and some interesting concepts are discussed. Our study shows how FCA can help the domain experts in the exploration of complex data.

Mots clés: Formal Concept Analysis; Knowledge Discovery; Transcriptomic Data.; Transcriptomic Data

Domaines: Intelligence artificielle [cs.AI]

Mehwish Alam, Adrien Coulet, Amedeo Napoli, Malika Smaïl-Tabbone. Formal Concept Analysis Applied to Transcriptomic Data. The Ninth International Conference on Concept Lattices and Their Applications - CLA 2012, Oct 2012, Fuengirola (Málaga), Spain. ⟨hal-00761003⟩