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Tensor clustering with algebraic constraints gives interpretable groups of crosstalk mechanisms in breast cancer
We introduce a tensor-based clustering method to extract sparse, low-dimensional structure from high-dimensional, multi-indexed datasets. This framework is designed to enable detection of clusters of data in the presence of structural requirements which we encode as algebraic constraints in a linear...
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| I publikationen: | J R Soc Interface |
|---|---|
| Huvudupphovsmän: | , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
The Royal Society
2019
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6408352/ https://ncbi.nlm.nih.gov/pubmed/30958184 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rsif.2018.0661 |
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