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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/19200

Title: Integrated analysis of multi-source data in drug discovery experiments using structural equation models
Authors: BIGIRUMURAME, Theophile
KASIM, Adetayo
Issue Date: 2015
Citation: Kepler, Johannes (Ed.) Proceedings of the 30th International Workshop on Statistical Modelling, p. 39-42
Series/Report no.: 2
Abstract: The drug discovery and development processes are typically costly and time consuming. Hence, it is crucial to identify early failure of candidate compounds and thereby save time and investment in a later stage. We propose structural equation modeling (SEM) based approach for an integrated analysis which combines information from three data sources: (1) bioactivity variables, (2) variables representing the chemical structure of the compounds, and (3) gene expression data. The proposed model allows to estimate the effects of the gene expression on the biological activity variable and furthermore, it allows to decompose the effect of the chemical structure on the biological activity into direct and indirect (i.e. the effect via the gene expression) effects.
URI: http://hdl.handle.net/1942/19200
Link to publication: http://ifas.jku.at/iwsm2015/proceedings/
Category: C2
Type: Proceedings Paper
Appears in Collections: Research publications

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