Abstract
The present work visualizes and interprets gene expression data of arthritic patients using the mathematical theory of Formal Concept Analysis (FCA). For the purpose of representing gene expression processes we employ the branch of Temporal Concept Analysis (TCA) which has been introduced during the last ten years in order to support conceptual reasoning about temporal phenomena. In TCA, movements of general objects in abstract or “real” space and time can be described in a conceptual framework. For our purpose in this paper we only need a special case of the general notion of a Conceptual Semantic System (CSS), namely a Conceptual Time System with actual Objects and a Time relation (CTSOT). In the theory of CTSOTs, there are clear mathematical definitions of notions of objects, states, situations, transitions and life tracks. It is very important for our application that these notions are compatible with the granularity of the chosen scaling of the original data.
This paper contributes to the biomedical study of disease processes in rheumatoid arthritis (RA) and the inflammatory disease control osteo-arthritis (OA), focusing on their molecular regulation. Time series of messenger RNA (mRNA) concentration levels in synovial cells from RA and OA patients were measured for a period of 12 hours after cytokine stimulation. These data are represented simultaneously as life tracks in transition diagrams of concept lattices constructed from the mRNA measurements for small sets of interesting genes. Biologically interesting differences between the two groups of patients are revealed. The transition diagrams are compared to literature and expert knowledge in order to explain the observed transitions by influences of certain proteins on gene transcription and to deduce new hypotheses concerning gene regulation.
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Wollbold, J., Huber, R., Kinne, R., Wolff, K.E. (2011). Conceptual Representation of Gene Expression Processes. In: Wolff, K.E., Palchunov, D.E., Zagoruiko, N.G., Andelfinger, U. (eds) Knowledge Processing and Data Analysis. KPP KONT 2007 2007. Lecture Notes in Computer Science(), vol 6581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22140-8_6
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