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Juarez, Reecan J., Jiang, Yaoyukun, Tremblay, Matthew, Shao, Qianzhen, Link, A. James, Yang, Zhongyue J. (2023) LassoHTP: A High-Throughput Computational Tool for Lasso Peptide Structure Construction and Modeling. Journal of Chemical Information and Modeling, 63 (2) 522-530 doi:10.1021/acs.jcim.2c00945

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Reference TypeJournal (article/letter/editorial)
TitleLassoHTP: A High-Throughput Computational Tool for Lasso Peptide Structure Construction and Modeling
JournalJournal of Chemical Information and Modeling
AuthorsJuarez, Reecan J.Author
Jiang, YaoyukunAuthor
Tremblay, MatthewAuthor
Shao, QianzhenAuthor
Link, A. JamesAuthor
Yang, Zhongyue J.Author
Year2023 (January 23)Volume63
Issue2
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jcim.2c00945Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15679547Long-form Identifiermindat:1:5:15679547:2
GUID0
Full ReferenceJuarez, Reecan J., Jiang, Yaoyukun, Tremblay, Matthew, Shao, Qianzhen, Link, A. James, Yang, Zhongyue J. (2023) LassoHTP: A High-Throughput Computational Tool for Lasso Peptide Structure Construction and Modeling. Journal of Chemical Information and Modeling, 63 (2) 522-530 doi:10.1021/acs.jcim.2c00945
Plain TextJuarez, Reecan J., Jiang, Yaoyukun, Tremblay, Matthew, Shao, Qianzhen, Link, A. James, Yang, Zhongyue J. (2023) LassoHTP: A High-Throughput Computational Tool for Lasso Peptide Structure Construction and Modeling. Journal of Chemical Information and Modeling, 63 (2) 522-530 doi:10.1021/acs.jcim.2c00945
In(2023, January) Journal of Chemical Information and Modeling Vol. 63 (2) American Chemical Society (ACS)


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