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BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning.
Prihoda, David; Maamary, Jad; Waight, Andrew; Juan, Veronica; Fayadat-Dilman, Laurence; Svozil, Daniel; Bitton, Danny A.
Affiliation
  • Prihoda D; Department of Informatics and Chemistry, University of Chemistry and Technology, Prague, Czech Republic.
  • Maamary J; R&D Informatics Solutions, MSD Czech Republic S.r.o, Prague, Czech Republic.
  • Waight A; Predictive and Clinical Immunogenicity, Merck & Co., Inc, Kenilworth, New Jersey, USA.
  • Juan V; Discovery Biologics, Protein Sciences, MRL, Merck & Co., Inc, South San Francisco, CA, USA.
  • Fayadat-Dilman L; Discovery Biologics, Protein Sciences, MRL, Merck & Co., Inc, South San Francisco, CA, USA.
  • Svozil D; Discovery Biologics, Protein Sciences, MRL, Merck & Co., Inc, South San Francisco, CA, USA.
  • Bitton DA; Department of Informatics and Chemistry, University of Chemistry and Technology, Prague, Czech Republic.
MAbs ; 14(1): 2020203, 2022.
Article in En | MEDLINE | ID: mdl-35133949
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Guideline / Prognostic_studies Limits: Animals Language: En Journal: MAbs Journal subject: ALERGIA E IMUNOLOGIA Year: 2022 Type: Article Affiliation country: Czech Republic
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Guideline / Prognostic_studies Limits: Animals Language: En Journal: MAbs Journal subject: ALERGIA E IMUNOLOGIA Year: 2022 Type: Article Affiliation country: Czech Republic