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  "Title": "A Supervised Approach for **P**r**e**dicting **c**ell Cycle\nPr**o**gression using scRNA-seq data",
  "Authors@R": "c(\nperson(\"Chiaowen Joyce\",\"Hsiao\", email=\"joyce.hsiao1@gmail.com\",\nrole=c(\"aut\",\"cre\")),\nperson(\"Matthew\", \"Stephens\", email=\"stephens999@gmail.com\", role=\"aut\"),\nperson(\"John\", \"Blischak\", email = \"jdblischak@gmail.com\", role=\"ctb\"),\nperson(\"Peter\", \"Carbonetto\", email = \"peter.carbonetto@gmail.com\",\nrole=\"ctb\"))",
  "Description": "Our approach provides a way to assign continuous cell\ncycle phase using scRNA-seq data, and consequently, allows to\nidentify cyclic trend of gene expression levels along the cell\ncycle. This package provides method and training data, which\nincludes scRNA-seq data collected from 6 individual cell lines\nof induced pluripotent stem cells (iPSCs), and also continuous\ncell cycle phase derived from FUCCI fluorescence imaging data.",
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