In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements.

MLA

Mattei, Aimee E., et al. “In Silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in Silico Algorithm Infrastructure and a Vision for Future Enhancements.” Frontiers in Drug Discovery, vol. 2, 2022. EBSCOhost, https://doi.org/10.3389/fddsv.2022.952326.

APA

Mattei, A. E., Gutierrez, A. H., Martin, W. D., Terry, F. E., Roberts, B. J., Rosenberg, A. S., & De Groot, A. S. (2022). In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements. Frontiers in Drug Discovery, 2. https://doi.org/10.3389/fddsv.2022.952326

Chicago

Mattei, Aimee E, Andres H Gutierrez, William D Martin, Frances E Terry, Brian J Roberts, Amy S Rosenberg, and Anne S De Groot. 2022. “In Silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in Silico Algorithm Infrastructure and a Vision for Future Enhancements.” Frontiers in Drug Discovery 2. doi:10.3389/fddsv.2022.952326.