Agent-Based Models Help Interpret Patterns of Clinical Drug Resistance by Contextualizing Competition Between Distinct Drug Failure Modes.

MLA

Leighow, Scott M., et al. “Agent-Based Models Help Interpret Patterns of Clinical Drug Resistance by Contextualizing Competition Between Distinct Drug Failure Modes.” Cellular & Molecular Bioengineering, vol. 15, no. 5, Oct. 2022, pp. 521–33. EBSCOhost, https://doi.org/10.1007/s12195-022-00748-6.

APA

Leighow, S. M., Landry, B., Lee, M. J., Peyton, S. R., & Pritchard, J. R. (2022). Agent-Based Models Help Interpret Patterns of Clinical Drug Resistance by Contextualizing Competition Between Distinct Drug Failure Modes. Cellular & Molecular Bioengineering, 15(5), 521–533. https://doi.org/10.1007/s12195-022-00748-6

Chicago

Leighow, Scott M., Ben Landry, Michael J. Lee, Shelly R. Peyton, and Justin R. Pritchard. 2022. “Agent-Based Models Help Interpret Patterns of Clinical Drug Resistance by Contextualizing Competition Between Distinct Drug Failure Modes.” Cellular & Molecular Bioengineering 15 (5): 521–33. doi:10.1007/s12195-022-00748-6.