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    ARTICLE

    Machine learning and bioinformatics to identify biomarkers in response to Burkholderia pseudomallei infection in mice

    YAO FANG1,2,#, FEI XIA1,#, FEIFEI TIAN3, LEI QU1, FANG YANG1, JUAN FANG1,2, ZHENHONG HU1,*, HAICHAO LIU1,*

    BIOCELL, Vol.48, No.4, pp. 613-621, 2024, DOI:10.32604/biocell.2024.031539

    Abstract Objective: In the realm of Class I pathogens, Burkholderia pseudomallei (BP) stands out for its propensity to induce severe pathogenicity. Investigating the intricate interactions between BP and host cells is imperative for comprehending the dynamics of BP infection and discerning biomarkers indicative of the host cell response process. Methods: mRNA extraction from BP-infected mouse macrophages constituted the initial step of our study. Employing gene expression arrays, the extracted RNA underwent conversion into digital signals. The percentile shift method facilitated data processing, with the identification of genes manifesting significant differences accomplished through the application of the t-test. Subsequently, a comprehensive analysis… More >

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