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Rapid Communication | Open Access

DARG: An integrated knowledge base for analyzing addictive drug-related genes

Xu WangBei YunZihan ZhangXiaoxi WangYifan WuYubo HuShiyi FangJunjie LvLina Chen( )Wan Li( )
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China

Peer review under responsibility of Chongqing Medical University.

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References

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Guo AY, Webb BT, Miles MF, Zimmerman MP, Kendler KS, Zhao Z. ERGR: an ethanol-related gene resource. Nucleic Acids Res. 2009;37(Database issue):D840-D845.

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Shi L, Wang Y, Li C, Zhang K, Du Q, Zhao M. AddictGene: an integrated knowledge base for differentially expressed genes associated with addictive substance. Comput Struct Biotechnol J. 2021;19:2416-2422.

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Wang X, Sun S, Chen H, et al. Identification of key genes and therapeutic drugs for cocaine addiction using integrated bioinformatics analysis. Front Neurosci. 2023;17:1201897.

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Ren X, Kuan PF. methylGSA: a Bioconductor package and Shiny app for DNA methylation data length bias adjustment in gene set testing. Bioinformatics. 2019;35(11):1958-1959.

Genes & Diseases
Article number: 101369
Cite this article:
Wang X, Yun B, Zhang Z, et al. DARG: An integrated knowledge base for analyzing addictive drug-related genes. Genes & Diseases, 2025, 12(2): 101369. https://doi.org/10.1016/j.gendis.2024.101369

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Received: 15 January 2024
Published: 28 June 2024
© 2024 The Authors.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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