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CLARITY: comparing heterogeneous data using dissimilarity
Integrating datasets from different disciplines is hard because the data are often qualitatively different in meaning, scale and reliability. When two datasets describe the same entities, many scientific questions can be phrased around whether the (dis)similarities between entities are conserved acr...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8652278/ https://www.ncbi.nlm.nih.gov/pubmed/34909208 http://dx.doi.org/10.1098/rsos.202182 |