Article Information
History
- July 28, 2022.
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
Author Information
- Simon Roux1,*,
- Antonio Pedro Camargo1,
- Felipe H. Coutinho2,
- Shareef M. Dabdoub3,
- Bas E. Dutilh4,5,
- Stephen Nayfach1 and
- Andrew Tritt6
- 1DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- 2Instituto de Ciencias del Mar (ICM-CSIC), Barcelona, Spain
- 3Division of Biostatistics and Computational Biology, University of Iowa College of Dentistry, Iowa City, IA, USA
- 4Institute of Biodiversity, Faculty of Biological Sciences, Cluster of Excellence Balance of the Microverse, Friedrich Schiller University, Rosalind Franklin Strasse 1, 07743, Jena, Germany
- 6Theoretical Biology and Bioinformatics, Science for Life, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands
- 6Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- ↵*Correspondence to: sroux{at}lbl.gov
Posted July 28, 2022.
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes
