Cargando…
Structure-revealing data fusion
BACKGROUND: Analysis of data from multiple sources has the potential to enhance knowledge discovery by capturing underlying structures, which are, otherwise, difficult to extract. Fusing data from multiple sources has already proved useful in many applications in social network analysis, signal proc...
Autores principales: | Acar, Evrim, Papalexakis, Evangelos E, Gürdeniz, Gözde, Rasmussen, Morten A, Lawaetz, Anders J, Nilsson, Mathias, Bro, Rasmus |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4117975/ https://www.ncbi.nlm.nih.gov/pubmed/25015427 http://dx.doi.org/10.1186/1471-2105-15-239 |
Ejemplares similares
-
Data fusion in metabolomic cancer diagnostics
por: Bro, Rasmus, et al.
Publicado: (2012) -
Unraveling Diagnostic Biomarkers of Schizophrenia Through Structure-Revealing Fusion of Multi-Modal Neuroimaging Data
por: Acar, Evrim, et al.
Publicado: (2019) -
The Anatomy of American Football: Evidence from 7 Years of NFL Game Data
por: Pelechrinis, Konstantinos, et al.
Publicado: (2016) -
Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies
por: Thorsen, Jonathan, et al.
Publicado: (2016) -
Adaptive granularity in tensors: A quest for interpretable structure
por: Pasricha, Ravdeep S., et al.
Publicado: (2022)