Abstract
DNA micro-arrays are a mechanism for eliciting gene expression values, the concentration of the transcription products of a set of genes, under different chemical conditions. The phenomena of interest—up-regulation, down-regulation and co-regulation—are hypothesized to stem from the functional relationships among transcription products.
In [1,2,3] a generalisation of Formal Concept Analysis was developed with data mining applications in mind, \(\mathcal{K}\)-Formal Concept Analysis, where incidences take values in certain kinds of semirings, instead of the usual Boolean carrier set. In this paper, we use (\(\overline{\mathbb{R}}_{min, +}\))- and (\(\overline{\mathbb{R}}_{max, +}\)) to analyse gene expression data for Arabidopsis thaliana. We introduce the mechanism to render the data in the appropriate algebra and profit by the wealth of different Galois Connections available in Generalized Formal Concept Analysis to carry different analysis for up- and down-regulated genes.
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Valverde-Albacete, F.J., Peláez-Moreno, C.: Towards a generalisation of Formal Concept Analysis for data mining purposes. In: Missaoui, R., Schmidt, J. (eds.) Formal Concept Analysis. LNCS (LNAI), vol. 3874, pp. 161–176. Springer, Heidelberg (2006)
Valverde-Albacete, F.J., Peláez-Moreno, C.: Further Galois connections between semimodules over idempotent semirings. In: Diatta, J., Eklund, P. (eds.) Proceedings of the 4th Conference on Concept Lattices and Applications (CLA 2007), Montpellier, pp. 199–212 (2007)
Valverde-Albacete, F.J., Peláez-Moreno, C.: Extending conceptualisation modes for generalised Formal Concept Analysis. Information Sciences (in press)
Stoughton, R.: Applications of DNA microarrays in biology. Biochemistry 74, 53 (2005)
Yevtushenko, S.A.: System of data analysis “Concept Explorer”. In: [17], pp. 127–134 (in Russian), http://sourceforge.net/projects/conexp
Van Hoewyk, D., Takahashi, H., Inoue, E., Hess, A., Tamaoki, M., Pilon-Smits, E.A.H.: Transcriptome analyses give insights into Selenium-stress responses and Selenium tolerance mechanisms in arabidopsis. Physiologia Plantarum 132, 236–253 (2008)
Affymetrix. Statistical algorithms description document, Santa Clara, Ca (2002)
Gentleman, R., Carey, V., Huber, W., Irizarry, R., Dudoit, S. (eds.): Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Statistics for Biology and Health. Springer, Heidelberg (2005)
Irizarry, R.A.: Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Research 31, 15e–15 (2003)
Pensa, R., Besson, J., Boulicaut, J.: A methodology for biologically relevant pattern discovery from gene expression data. In: Suzuki, E., Arikawa, S. (eds.) DS 2004. LNCS (LNAI), vol. 3245, pp. 230–241. Springer, Heidelberg (2004)
Motameny, S., Versmold, B., Schmutzler, R.: Formal Concept Analysis for the identification of combinatorial biomarkers in breast cancer. In: Medina, R., Obiedkov, S. (eds.) ICFCA 2008. LNCS (LNAI), vol. 4933, pp. 229–240. Springer, Heidelberg (2008)
Gebert, J., Motameny, S., Faigle, U., Forst, C., Schrader, R.: Identifying genes of gene regulatory networks using Formal Concept Analysis. Journal of Computational Biology 15, 185–194 (2008)
Kaytoue, M., Duplessis, S., Kuznetsov, S.O., Napoli, A.: Two FCA-based methods for mining gene expression data. In: Ferré, S., Rudolph, S. (eds.) ICFCA 2009. LNCS, vol. 5548, pp. 251–266. Springer, Heidelberg (2009)
Pensa, R., Boulicaut, J.: Towards Fault-Tolerant Formal Concept Analysis. In: Bandini, S., Manzoni, S. (eds.) AI*IA 2005. LNCS (LNAI), vol. 3673, pp. 212–223. Springer, Heidelberg (2005)
Kaytoue, M., Kuznetsov, S., Napoli, A., Duplessis, S.: Mining gene expression data with pattern structures in Formal Concept Analysis. In: Information Sciences (2011)
Ganter, B., Kuznetsov, S.: Pattern structures and their projections. In: Delugach, H.S., Stumme, G. (eds.) ICCS 2001. LNCS (LNAI), vol. 2120, pp. 129–142. Springer, Heidelberg (2001)
ACM: Proceedings of the 7th National Conference on Artificial Intelligence KII 2000, Russia, ACM (2000)
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González Calabozo, J.M., Peláez-Moreno, C., Valverde-Albacete, F.J. (2011). Gene Expression Array Exploration Using \(\mathcal{K}\)-Formal Concept Analysis. In: Valtchev, P., Jäschke, R. (eds) Formal Concept Analysis. ICFCA 2011. Lecture Notes in Computer Science(), vol 6628. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20514-9_11
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DOI: https://doi.org/10.1007/978-3-642-20514-9_11
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