دورية أكاديمية
A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei
| العنوان: | A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei |
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| المؤلفون: | Phillip, Jude M., Han, Kyu-Sang, Chen, Wei-Chiang, Wirtz, Denis, Wu, Pei-Hsun |
| المساهمون: | U.S. Department of Health & Human Services | NIH | National Cancer Institute, U.S. Department of Health & Human Services | NIH | National Institute on Aging |
| المصدر: | Nature Protocols ; volume 16, issue 2, page 754-774 ; ISSN 1754-2189 1750-2799 |
| بيانات النشر: | Springer Science and Business Media LLC |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | General Biochemistry, Genetics and Molecular Biology |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.1038/s41596-020-00432-x |
| الإتاحة: | https://doi.org/10.1038/s41596-020-00432-xTest https://www.nature.com/articles/s41596-020-00432-x.pdfTest https://www.nature.com/articles/s41596-020-00432-xTest |
| حقوق: | https://www.springernature.com/gp/researchers/text-and-data-miningTest ; https://www.springernature.com/gp/researchers/text-and-data-miningTest |
| رقم الانضمام: | edsbas.194EFC6D |
| قاعدة البيانات: | BASE |
| DOI: | 10.1038/s41596-020-00432-x |
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