Formal concept analysis applied to transcriptomic data

Mehwish Alam, Adrien Coulet, Amedeo Napoli, Malika Smaïl-Tabbone

Research output: Contribution to journalConference articlepeer-review

Abstract

Identifying functions or pathways shared by genes responsi- ble for cancer is still a challenging task. This paper describes the prepa- ration work for applying Formal Concept Analysis (FCA) to biological data. After gene transcription experiments, we integrate various annota- tions of selected genes in a database along with relevant domain knowl- edge. The database subsequently allows to build formal contexts in a exible way. We present here a preliminary experiment using these data on a core context with the addition of domain knowledge by context ap- position. The resulting concept lattices are pruned and we discuss some interesting concepts. Our study shows how data integration and FCA can help the domain expert in the exploration of complex data.

Original languageEnglish
Pages (from-to)7-14
Number of pages8
JournalCEUR Workshop Proceedings
Volume939
Publication statusPublished - 1 Dec 2012
Externally publishedYes
EventInternational Workshop "What Can FCA Do for Artificial Intelligence?", FCA4AI 2012 - Workshop of the ECAI 2012 Conference - Montpellier, France
Duration: 28 Aug 201228 Aug 2012

Keywords

  • Data in- tegration
  • Formal concept analysis
  • Knowledge discovery
  • Transcriptomic data

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