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Peer-reviewedLicence not statedNature Methods

Efficient evidence-based genome annotation with EviAnn

  • Aleksey V. Zimin1,2
  • Daniela Puiu3,4
  • Mihaela Pertea3,4
  • James A. Yorke5
  • Steven L. Salzberg3,4,6,7
7 affiliations
  1. 1Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA. [email protected]
  2. 2Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. [email protected]
  3. 3Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
  4. 4Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
  5. 5Department of Mathematics, University of Maryland, College Park, MD, USA
  6. 6Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
  7. 7Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
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Cite

BibTeXRIS
BibTeX
@article{zimin2026efficient,
  title = {{Efficient evidence-based genome annotation with EviAnn}},
  author = {Aleksey V. Zimin and Daniela Puiu and Mihaela Pertea and James A. Yorke and Steven L. Salzberg},
  journal = {Nature Methods},
  year = {2026},
  month = jul,
  doi = {10.1038/s41592-026-03156-0},
  url = {https://doi.org/10.1101/2025.05.07.652745},
}
RIS
TY  - JOUR
TI  - Efficient evidence-based genome annotation with EviAnn
AU  - Aleksey V. Zimin
AU  - Daniela Puiu
AU  - Mihaela Pertea
AU  - James A. Yorke
AU  - Steven L. Salzberg
PY  - 2026
DA  - 2026/07/03
JO  - Nature Methods
DO  - 10.1038/s41592-026-03156-0
UR  - https://doi.org/10.1101/2025.05.07.652745
SN  - 1548-7091
SN  - 1548-7105
ER  -