AI-EPI: Atlas-level Integrated Epithelial Program Identification
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2025
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| author | Zhou, Tao Wu, Yanhong Li, Shuai Gu, Jin Chen, Lei |
| author_facet | Zhou, Tao Wu, Yanhong Li, Shuai Gu, Jin Chen, Lei |
| contents | <p>Malignant epithelial cells are the most heterogeneous cell type with almost every patient forming a separate cluster. Here, we present a method, AI-EPI (<strong>A</strong>tlas-level <strong>I</strong>ntegrated <strong>E</strong>pithelial <strong>P</strong>rogram <strong>I</strong>dentification), which identifies patient-shared and patient-specific gene modules (GM) simultaneously and efficiently.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15406569 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI-EPI: Atlas-level Integrated Epithelial Program Identification Zhou, Tao Wu, Yanhong Li, Shuai Gu, Jin Chen, Lei <p>Malignant epithelial cells are the most heterogeneous cell type with almost every patient forming a separate cluster. Here, we present a method, AI-EPI (<strong>A</strong>tlas-level <strong>I</strong>ntegrated <strong>E</strong>pithelial <strong>P</strong>rogram <strong>I</strong>dentification), which identifies patient-shared and patient-specific gene modules (GM) simultaneously and efficiently.</p> |
| title | AI-EPI: Atlas-level Integrated Epithelial Program Identification |
| url | https://doi.org/10.5281/zenodo.15406569 |