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FrameRate: learning the coding potential of unassembled metagenomic reads
View ORCID ProfileWang Liu-Wei, View ORCID ProfileWayne Aubrey, View ORCID ProfileAmanda Clare, View ORCID ProfileRobert Hoehndorf, View ORCID ProfileChristopher J. Creevey, View ORCID ProfileNicholas J. Dimonaco
doi: https://doi.org/10.1101/2022.09.16.508314
Wang Liu-Wei
1Systems Medicine of Infectious Disease (P5), Robert Koch Institute, Berlin, Germany
2International Max-Planck Research School for Biology and Computing (IMPRS-BAC), Berlin, Germany
Wayne Aubrey
3Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, Wales, UK
Amanda Clare
3Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, Wales, UK
Robert Hoehndorf
4Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
Christopher J. Creevey
5School of Biological Sciences, Queen’s University Belfast, Belfast, BT7 1NN, Northern Ireland, UK
Nicholas J. Dimonaco
3Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, Wales, UK
6Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, SY23 3PD, Wales, UK
Posted September 19, 2022.
FrameRate: learning the coding potential of unassembled metagenomic reads
Wang Liu-Wei, Wayne Aubrey, Amanda Clare, Robert Hoehndorf, Christopher J. Creevey, Nicholas J. Dimonaco
bioRxiv 2022.09.16.508314; doi: https://doi.org/10.1101/2022.09.16.508314
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