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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 ofdoi:10.1186/1471-2105-15-113 pmid:24742351 pmcid:PMC4011783 fatcat:mbxzgdvc6jgx3l6i47jufpcvqi