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...

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Detalles Bibliográficos
Autores principales: Lawson, Daniel J., Solanki, Vinesh, Yanovich, Igor, Dellert, Johannes, Ruck, Damian, Endicott, Phillip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Mathematics
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

Internet

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

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