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http://hdl.handle.net/1942/19200
Title: | Integrated analysis of multi-source data in drug discovery experiments using structural equation models | Authors: | BIGIRUMURAME, Theophile PERUALILA, Nolen Joy SHKEDY, Ziv KASIM, Adetayo |
Issue Date: | 2015 | Source: | 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. | Keywords: | structural equation modeling; microarray data; bioassays | Document URI: | http://hdl.handle.net/1942/19200 | Link to publication/dataset: | http://ifas.jku.at/iwsm2015/proceedings/ | Category: | C2 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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Bigirumurame.pdf | Peer-reviewed author version | 208.52 kB | Adobe PDF | View/Open |
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