APA aipamena

Eyre, D., Cule, M., Griffiths, D., Crook, D., Peto, T., Walker, A., & Wilson, D. (2013). Detection of mixed infection from bacterial whole genome sequence data allows assessment of its role in Clostridium difficile transmission. Public Library of Science.

Chicago Style aipamena

Eyre, D., M. Cule, D. Griffiths, D. Crook, T. Peto, A. Walker, and D. Wilson. Detection of Mixed Infection from Bacterial Whole Genome Sequence Data Allows Assessment of Its Role in Clostridium Difficile Transmission. Public Library of Science, 2013.

MLA aipamena

Eyre, D., et al. Detection of Mixed Infection from Bacterial Whole Genome Sequence Data Allows Assessment of Its Role in Clostridium Difficile Transmission. Public Library of Science, 2013.