Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity.

Asti L, Uguzzoni G, Marcatili P, Pagnani A

DOI: 10.1371/journal.pcbi.1004870
Published: 2016 Apr
Container: PLoS computational biology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pcbi.1004870,
  title = {Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity.},
  author = {Asti L and Uguzzoni G and Marcatili P and Pagnani A},
  year = {2016},
  journal = {PLoS computational biology},
  doi = {10.1371/journal.pcbi.1004870},
  url = {https://doi.org/10.1371/journal.pcbi.1004870}
}

RIS

TY  - JOUR
TI  - Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity.
AU  - Asti L
AU  - Uguzzoni G
AU  - Marcatili P
AU  - Pagnani A
PY  - 2016
JO  - PLoS computational biology
DO  - 10.1371/journal.pcbi.1004870
UR  - https://doi.org/10.1371/journal.pcbi.1004870
ER  -

APA

L, A., G, U., P, M., & A, P. (2016). Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity.. PLoS computational biology. https://doi.org/10.1371/journal.pcbi.1004870

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pubmed · retrieved 2026-11-10T08:29:59.125Z