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Cited by 1vaccines and immunoinformatics approachesSARS-CoV-2 and COVID-19 ResearchMonoclonal and Polyclonal Antibodies Research

The DOI matches its Crossref record.

VAEResTL: A Novel Generative Model for Designing Complementarity Determining Region of Antibody for SARS-CoV-2

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Khalilian, Saeed, Moti, Zahra, Baloochestani, Arian, Hallaj, Yeganeh, Chavosh, Alireza, Hemmatian, Zahra·2022·Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies
DOI 10.5220/0010823700003123
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Crossref · 10.5220/0010823700003123

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Metadata

Authors
Khalilian, S., Moti, Z., Baloochestani, A., Hallaj, Y., Chavosh, A., & Hemmatian, Z.
Affiliations
  • Independent Researcher, Iran, --- Select a Country ---
  • Independent Researcher, The Netherlands, --- Select a Country ---
  • Independent Researcher, Norway, --- Select a Country ---
  • MarWell Bio Inc., California, U.S.A., --- Select a Country ---
ORCID
Khalilian, Saeed
Venue
Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies
Publisher
SCITEPRESS - Science and Technology Publications
Published
2022
Pages
107-114
DOI
10.5220/0010823700003123
OpenAlex
W4214873489
Cited by
1
References
0
Citations by year
2022: 1
FWCI
1.16
Type
conference paper
Language
en
Open access
Licence
cc-by-nc-nd
Locations
International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) (publishedVersion, cc-by-nc-nd)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
Keywords
hypervariable region, generative models, SARS-CoV-2, antibody design, protein structure prediction, deep learning

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CoChat. (2026). Citation check: VAEResTL: A Novel Generative Model for Designing Complementarity Determining Region of Antibody for SARS-CoV-2. https://app.cochat.ai/papers/10.5220/0010823700003123
The paper
Khalilian, S., Moti, Z., Baloochestani, A., Hallaj, Y., Chavosh, A., & Hemmatian, Z. (2022). VAEResTL: A Novel Generative Model for Designing Complementarity Determining Region of Antibody for SARS-CoV-2. Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies. https://doi.org/10.5220/0010823700003123