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SIMBA: SIngle-cell eMBedding Along with features
View ORCID ProfileHuidong Chen, View ORCID ProfileJayoung Ryu, View ORCID ProfileMichael Vinyard, Adam Lerer, View ORCID ProfileLuca Pinello
doi: https://doi.org/10.1101/2021.10.17.464750
Huidong Chen
1Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
2Department of Pathology, Harvard Medical School, Boston, MA, USA
3Broad Institute of Harvard and MIT, Cambridge, MA, USA
Jayoung Ryu
1Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
2Department of Pathology, Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
Michael Vinyard
1Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
2Department of Pathology, Harvard Medical School, Boston, MA, USA
3Broad Institute of Harvard and MIT, Cambridge, MA, USA
5Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
Adam Lerer
6Facebook AI Research
Luca Pinello
1Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
2Department of Pathology, Harvard Medical School, Boston, MA, USA
3Broad Institute of Harvard and MIT, Cambridge, MA, USA
Posted October 18, 2021.
SIMBA: SIngle-cell eMBedding Along with features
Huidong Chen, Jayoung Ryu, Michael Vinyard, Adam Lerer, Luca Pinello
bioRxiv 2021.10.17.464750; doi: https://doi.org/10.1101/2021.10.17.464750
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