{
 "id": "kahkengwong/CEP-IP_Framework",
 "owner": "kahkengwong",
 "name": "CEP-IP_Framework",
 "downloads": 128,
 "likes": 0,
 "last_modified": "2026-10-20T02:43:40.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
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 "citation": "If you use any of these processed datasets, please cite:\n\nWong KK (2026). CEP-IP: An explainable framework for cell subpopulation identification in single-cell transcriptomics. Computer Methods and Programs in Biomedicine, 282, 109372. https://doi.org/10.1016/j.cmpb.2026.109372\n\nPlease also cite the respective source datasets:\n\nWong HY, Sheng Q, Hesterberg AB, Croessmann S et al (2022). Single cell analysis of cribriform prostate cancer reveals cell intrinsic and tumor microenvironmental pathways of aggressive disease. Nat Commun 13(1):6036. https://doi.org/10.1038/s41467-022-33780-1\n\nHodge RD, Bakken TE, Miller JA, Smith KA et al (2019). Conserved cell types with divergent features in human versus mouse cortex. Nature 573:61-68. https://doi.org/10.1038/s41586-019-1506-7\n\nNeftel C, Laffy J, Filbin MG, Hara T et al (2019). An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma. Cell 178:835-849. https://doi.org/10.1016/j.cell.2019.06.024",
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 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "e62d95631bb06ad3b83f2f729c791f662ed90d6e",
 "stated_evidence": "https://huggingface.co/datasets/kahkengwong/CEP-IP_Framework/blob/e62d95631bb06ad3b83f2f729c791f662ed90d6e/README.md",
 "file_evidence": "https://huggingface.co/datasets/kahkengwong/CEP-IP_Framework/tree/e62d95631bb06ad3b83f2f729c791f662ed90d6e",
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}