American Psychological Association 6th edition

Hepler, N. L., Scheffler, K., Weaver, S., Murrell, B., Richman, D. D., Burton, D. R., Poignard, P., Smith, D. M., & Kosakovsky Pond, S. L. (2014). IDEPI: Rapid Prediction of HIV-1 Antibody Epitopes and Other Phenotypic Features from Sequence Data Using a Flexible Machine Learning Platform. PLo S Computational Biology, 10(9), 1-10. https://doi.org/10.1371/journal.pcbi.1003842

ISO-690 (author-date, English)

HEPLER, N. Lance, SCHEFFLER, Konrad, WEAVER, Steven, MURRELL, Ben, RICHMAN, Douglas D., BURTON, Dennis R., POIGNARD, Pascal, SMITH, Davey M. and KOSAKOVSKY POND, Sergei L., 2014. IDEPI: Rapid Prediction of HIV-1 Antibody Epitopes and Other Phenotypic Features from Sequence Data Using a Flexible Machine Learning Platform. PLo S Computational Biology. 1 September 2014. Vol. 10, no. 9, p. 1-10. DOI 10.1371/journal.pcbi.1003842.

Modern Language Association 9th edition

Hepler, N. L., K. Scheffler, S. Weaver, B. Murrell, D. D. Richman, D. R. Burton, P. Poignard, D. M. Smith, and S. L. Kosakovsky Pond. “IDEPI: Rapid Prediction of HIV-1 Antibody Epitopes and Other Phenotypic Features from Sequence Data Using a Flexible Machine Learning Platform.”. PLo S Computational Biology, vol. 10, no. 9, Sept. 2014, pp. 1-10, https://doi.org/10.1371/journal.pcbi.1003842.

Mohr Siebeck - Recht (Deutsch - Österreich)

Hepler, N. Lance/Scheffler, Konrad/Weaver, Steven/Murrell, Ben/Richman, Douglas D./Burton, Dennis R. et al.: IDEPI: Rapid Prediction of HIV-1 Antibody Epitopes and Other Phenotypic Features from Sequence Data Using a Flexible Machine Learning Platform., PLo S Computational Biology 2014, 1-10.

Emerald - Harvard

Hepler, N.L., Scheffler, K., Weaver, S., Murrell, B., Richman, D.D., Burton, D.R., Poignard, P., Smith, D.M. and Kosakovsky Pond, S.L. (2014), “IDEPI: Rapid Prediction of HIV-1 Antibody Epitopes and Other Phenotypic Features from Sequence Data Using a Flexible Machine Learning Platform.”, PLo S Computational Biology, Vol. 10 No. 9, pp. 1-10.

Warning: These citations may not always be 100% accurate.