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Neopepsee: accurate genome-level prediction of neoantigens by harnessing sequence and amino acid immunogenicity information.
Kim, S; Kim, H S; Kim, E; Lee, M G; Shin, E-C; Paik, S; Kim, S.
Affiliation
  • Kim S; Severance Biomedical Science Institute.
  • Kim HS; Department of Pharmacology, Pharmacogenomic Research Center for Membrane Transporters, Brain Korea 21 PLUS Project for Medical Sciences; Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul.
  • Kim E; Severance Biomedical Science Institute.
  • Lee MG; Department of Pharmacology, Pharmacogenomic Research Center for Membrane Transporters, Brain Korea 21 PLUS Project for Medical Sciences.
  • Shin EC; Graduate School of Medical Science and Engineering, KAIST, Daejeon, Korea.
  • Paik S; Severance Biomedical Science Institute; Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul.
  • Kim S; Severance Biomedical Science Institute. Electronic address: swkim@yuhs.ac.
Ann Oncol ; 29(4): 1030-1036, 2018 04 01.
Article in En | MEDLINE | ID: mdl-29360924
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome / Machine Learning / Antigens Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Ann Oncol Journal subject: NEOPLASIAS Year: 2018 Type: Article
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome / Machine Learning / Antigens Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Ann Oncol Journal subject: NEOPLASIAS Year: 2018 Type: Article