BMC Bioinformatics | |
Probabilistic drug connectivity mapping | |
Juuso A Parkkinen2  Samuel Kaski1  | |
[1] Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland | |
[2] Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland | |
关键词: Probabilistic modeling; Latent variable models; Gene expression; Data integration; Connectivity mapping; | |
Others : 818658 DOI : 10.1186/1471-2105-15-113 |
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received in 2013-12-18, accepted in 2014-04-14, 发布年份 2014 | |
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【 摘 要 】
Background
The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines. This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug. We infer the relevance for retrieval by data-driven probabilistic modeling of the drug responses, resulting in probabilistic connectivity mapping, and further consider the available cell lines as different data sources. We use a special type of probabilistic model to separate what is shared and specific between the sources, in contrast to earlier connectivity mapping methods that have intentionally aggregated all available data, neglecting information about the differences between the cell lines.
Results
We show that the probabilistic multi-source connectivity mapping method is superior to alternatives in finding functionally and chemically similar drugs from the Connectivity Map data set. We also demonstrate that an extension of the method is capable of retrieving combinations of drugs that match different relevant parts of the query drug response profile.
Conclusions
The probabilistic modeling-based connectivity mapping method provides a promising alternative to earlier methods. Principled integration of data from different cell lines helps to identify relevant responses for specific drug repositioning applications.
【 授权许可】
2014 Parkkinen and Kaski; licensee BioMed Central Ltd.
【 预 览 】
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