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A Self-Training Subspace Clustering Algorithm under Low-Rank Representation for Cancer Classification on Gene Expression Data
Accurate identification of the cancer types is essential to cancer diagnoses and treatments. Since cancer tissue and normal tissue have different gene expression, gene expression data can be used as an efficient feature source for cancer classification. However, accurate cancer classification direct...
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| Publicado en: | IEEE/ACM Trans Comput Biol Bioinform |
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| Autores principales: | , , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
2017
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5986621/ https://ncbi.nlm.nih.gov/pubmed/28600258 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TCBB.2017.2712607 |
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