Biomedical research takes advantage of omic data, such as transcriptomics, to unravel the complexity of diseases. A conventional strategy identifies transcriptomic biomarkers characterized by expression patterns associated with a phenotype by relying on feature selection approaches. Hybrid ensemble feature selection (HEFS) has become increasingly popular as it ensures robustness of the selected features by performing data and functional perturbations.
View Article and Find Full Text PDFIntracellular pathogens like Brucella face challenges during the intraphagocytic adaptation phase, where the modulation of gene expression plays an essential role in taking advantage of stressors to persist inside the host cell. This study aims to explore the expression of antisense virB2 RNA strand and related genes under intracellular simulation media. Sense and antisense virB2 RNA strands increased expression when nutrient deprivation and acidification were higher, being starvation more determinative.
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