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A hybrid unsupervised methodology on artificial intelligence filtering for automatically processing cellular DNA-encoded library (DEL) datasets

Yiran Huang et al.

Bioinformatics2026https://doi.org/10.1093/bioinformatics/btag001article
ABDC A
Weight
0.50

Abstract

The complete datasets, source code, and pre-trained models are made available at https://doi.org/10.5281/zenodo.17452392 and https://doi.org/10.5281/zenodo.17569557.

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https://doi.org/https://doi.org/10.1093/bioinformatics/btag001

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@article{yiran2026,
  title        = {{A hybrid unsupervised methodology on artificial intelligence filtering for automatically processing cellular DNA-encoded library (DEL) datasets}},
  author       = {Yiran Huang et al.},
  journal      = {Bioinformatics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/bioinformatics/btag001},
}

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A hybrid unsupervised methodology on artificial intelligence filtering for automatically processing cellular DNA-encoded library (DEL) datasets

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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

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