A transfer learning framework to elucidate the clinical relevance of altered proximal tubule cell states in kidney disease

Summary: The application of single-cell technologies in clinical nephrology remains elusive. We generated an atlas of transcriptionally defined cell types and cell states of human kidney disease by integrating single-cell signatures reported in the literature with newly generated signatures obtained...

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التفاصيل البيبلوغرافية

الحاوية / القاعدة:	iScience
المؤلفون الرئيسيون:	David Legouis, Anna Rinaldi, Daniele Malpetti, Gregoire Arnoux, Thomas Verissimo, Anna Faivre, Francesca Mangili, Andrea Rinaldi, Lorenzo Ruinelli, Jerome Pugin, Solange Moll, Luca Clivio, Marco Bolis, Sophie de Seigneux, Laura Azzimonti, Pietro E. Cippà
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	Elsevier 2024-03-01
الموضوعات:	Cell biology Integrative aspects of cell biology Transcriptomics Machine learning
الوصول للمادة أونلاين:	http://www.sciencedirect.com/science/article/pii/S2589004224004929