Chemical Descriptors and Deep Learning Embeddings for Scoring <i>de novo</i> Peptide Designs

Quentin Trolliet, Alex Abrudan, Aryan Bhasin, Yunguan Fu, Joao Paulo Euko, Cheng Zhang, Francesco Saccon

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DOI: 10.64898/2026.09.10.750670
Published: 2026-09-11
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Publisher: openRxiv
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Cite this work

BibTeX

@article{allodium:10.64898/2026.09.10.750670,
  title = {Chemical Descriptors and Deep Learning Embeddings for Scoring
                  <i>de novo</i>
                  Peptide Designs},
  author = {Quentin Trolliet and Alex Abrudan and Aryan Bhasin and Yunguan Fu and Joao Paulo Euko and Cheng Zhang and Francesco Saccon},
  year = {2026},
  doi = {10.64898/2026.09.10.750670},
  url = {https://doi.org/10.64898/2026.09.10.750670}
}

RIS

TY  - JOUR
TI  - Chemical Descriptors and Deep Learning Embeddings for Scoring
                  <i>de novo</i>
                  Peptide Designs
AU  - Quentin Trolliet
AU  - Alex Abrudan
AU  - Aryan Bhasin
AU  - Yunguan Fu
AU  - Joao Paulo Euko
AU  - Cheng Zhang
AU  - Francesco Saccon
PY  - 2026
DO  - 10.64898/2026.09.10.750670
UR  - https://doi.org/10.64898/2026.09.10.750670
ER  -

APA

Trolliet, Q., Abrudan, A., Bhasin, A., Fu, Y., Euko, J. P., Zhang, C., & Saccon, F. (2026). Chemical Descriptors and Deep Learning Embeddings for Scoring <i>de novo</i> Peptide Designs. https://doi.org/10.64898/2026.09.10.750670

Source records

crossref · retrieved 2026-09-25T12:29:50.944Z