Publications by authors named "Ray Walshe"

Simulations were carried out to analyze a promising new antimicrobial treatment strategy for targeting antibiotic-resistant bacteria called the β-lactamase-dependent prodrug delivery system. In this system, the antibacterial drugs are delivered as inactive precursors that only become activated after contact with an enzyme characteristic of many species of antibiotic-resistant bacteria (β-lactamase enzyme). The addition of an activation step contributes an extra layer of complexity to the system that can lead to unexpected emergent behavior.

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Article Synopsis
  • Eukaryotic promoter prediction is a challenging aspect of computational genomics, crucial for understanding genetic regulatory networks, and requires improved tools due to the growing sequence data.
  • A novel method is introduced that utilizes 128 unique DNA motifs and a Support Vector Machine (SVM) to effectively differentiate between promoter and non-promoter sequences across various organisms, achieving high accuracy rates and low false positives.
  • The study concludes that using 4-mer frequencies along with machine learning can significantly enhance the identification of RNA polymerase II promoters compared to existing methods.
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An agent-based model of bacteria-antibiotic interactions has been developed that incorporates the antibiotic-resistance mechanisms of Methicillin-Resistant Staphylococcus aureus (MRSA). The model, called the Micro-Gen Bacterial Simulator, uses information about the cell biology of bacteria to produce global information about population growth in different environmental conditions. It facilitates a detailed systems-level investigation of the dynamics involved in bacteria-antibiotic interactions and a means to relate this information to traditional high-level properties such as the Minimum Inhibitory Concentration (MIC) of an antibiotic.

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