國家衛生研究院 NHRI:Item 3990099045/16071
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    题名: Incorporating tissue-specific gene expression data to improve chemical-disease inference of in silico toxicogenomics methods
    作者: Wang, SS;Wang, CC;Wang, CL;Lin, YC;Tung, CW
    贡献者: Institute of Biotechnology and Pharmaceutical Research;NHRI Graduate Student Program
    摘要: In silico toxicogenomics methods are resource- and time-efficient approaches for inferring chemical-protein-disease associations with potential mechanism information for exploring toxicological effects. However, current in silico toxicogenomics systems make inferences based on only chemical-protein interactions without considering tissue-specific gene/protein expressions. As a result, inferred diseases could be overpredicted with false positives. In this work, six tissue-specific expression datasets of genes and proteins were collected from the Expression Atlas. Genes were then categorized into high, medium, and low expression levels in a tissue- and dataset-specific manner. Subsequently, the tissue-specific expression datasets were incorporated into the chemical-protein-disease inference process of our ChemDIS system by filtering out relatively low-expressed genes. By incorporating tissue-specific gene/protein expression data, the enrichment rate for chemical-disease inference was largely improved with up to 62.26% improvement. A case study of melamine showed the ability of the proposed method to identify more specific disease terms that are consistent with the literature. A user-friendly user interface was implemented in the ChemDIS system. The methodology is expected to be useful for chemical-disease inference and can be implemented for other in silico toxicogenomics tools.
    日期: 2024-07-31
    關聯: Journal of Xenobiotics. 2024 Jul 31;14(3):1023-1035.
    Link to: http://dx.doi.org/10.3390/jox14030057
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=2039-4705&DestApp=IC2JCR
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85205255198
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