Drug Similarity Search Based on Combined Signatures in Gene Expression Profiles

차기훈; 김민성; 오기민; 신현정; 이관수

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자료유형: 학술저널

저자정보: 차기훈 김민성 오기민 신현정 이관수

저널정보: 대한의료정보학회 Healthcare Informatics Research Healthcare Informatics Research 제20권 제1호

발행연도: 2014.1

수록면: 52 - 60 (9page)

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Objectives: Recently, comparison of drug responses on gene expression has been a major approach to identifying the functional similarity of drugs. Previous studies have mostly focused on a single feature, the expression differences of individual genes. We provide a more robust and accurate method to compare the functional similarity of drugs by diversifying the features of comparison in gene expression and considering the sample dependent variations. Methods: For differentially expressed gene measurement, we modified the conventional t-test to normalize variations in diverse experimental conditions of individual samples. To extract significant differentially co-expressed gene modules, we searched maximal cliques among the co-expressed gene network. Finally, we calculated a combined similarity score by averaging the two scaled scores from the above two measurements. Results: This method shows significant performance improvement in comparison to other approaches in the test with Connectivity Map data. In the test to find the drugs based on their own expression profiles with leave-one-out cross validation, the proposed method showed an area under the curve (AUC) score of 0.99, which is much higher than scores obtained with previous methods, ranging from 0.71 to 0.93. In the drug networks, we could find well clustered drugs having the same target proteins and novel relations among drugs implying the possibility of drug repurposing. Conclusions: Inclusion of the features of a co-expressed module provides more implications to infer drug action. We propose that this method be used to find collaborative cellular mechanisms associated with drug action and to simply identify drugs having similar responses.

#Pharmacological Biomarkers #Transcriptome #Gene Expression Regulation #Gene Regulatory Networks #Drug Repositioning

참고문헌 (18)

참고문헌 신청

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