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Evaluating deep learning based structure prediction methods on antibody–antigen complexes

Samuel Fromm et al.

Bioinformatics2026https://doi.org/10.1093/bioinformatics/btag136article
ABDC A
Weight
0.50

Abstract

All code is available from github.com/samuelfromm/abag-benchmark-set/ and all data from DOI: 10.5281/zenodo.17978681. The latter repository also contains the code.

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https://doi.org/https://doi.org/10.1093/bioinformatics/btag136

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@article{samuel2026,
  title        = {{Evaluating deep learning based structure prediction methods on antibody–antigen complexes}},
  author       = {Samuel Fromm et al.},
  journal      = {Bioinformatics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/bioinformatics/btag136},
}

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Evaluating deep learning based structure prediction methods on antibody–antigen complexes

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.