AIMC Topic: Virulence Factors
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DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.
Briefings in bioinformatics
May 20, 2021
Virulence factors (VFs) enable pathogens to infect their hosts. A wealth of individual, disease-focused studies has identified a wide variety of VFs, and the growing mass of bacterial genome sequence data provides an opportunity for computational met...
Predicting bacterial virulence factors - evaluation of machine learning and negative data strategies.
Briefings in bioinformatics
Sep 25, 2020
Bacterial proteins dubbed virulence factors (VFs) are a highly diverse group of sequences, whose only obvious commonality is the very property of being, more or less directly, involved in virulence. It is therefore tempting to speculate whether their...
Learning transferable deep convolutional neural networks for the classification of bacterial virulence factors.
Bioinformatics (Oxford, England)
Jun 1, 2020
MOTIVATION: Identification of virulence factors (VFs) is critical to the elucidation of bacterial pathogenesis and prevention of related infectious diseases. Current computational methods for VF prediction focus on binary classification or involve on...
Victors: a web-based knowledge base of virulence factors in human and animal pathogens.
Nucleic acids research
Jan 8, 2019
Virulence factors (VFs) are molecules that allow microbial pathogens to overcome host defense mechanisms and cause disease in a host. It is critical to study VFs for better understanding microbial pathogenesis and host defense mechanisms. Victors (ht...
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