Diffusion enables integration of heterogeneous data and user-driven learning in a desktop knowledge-base.
Integrating reference datasets (e.g. from high-throughput experiments) with unstructured and manually-assembled information (e.g. notes or comments from individual researchers) has the potential to tailor bioinformatic analyses to specific needs and to lead to new insights. However, developing bespo...
Guardado en:
Autores principales: | Tomasz Konopka, Sandra Ng, Damian Smedley |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/bb4fd93ff8bb47818fb09c818b31bc10 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
3D virtual reality vs. 2D desktop registration user interface comparison.
por: Andreas Bueckle, et al.
Publicado: (2021) -
3D virtual reality vs. 2D desktop registration user interface comparison
por: Andreas Bueckle, et al.
Publicado: (2021) -
OmniCrawl: Comprehensive Measurement of Web Tracking With Real Desktop and Mobile Browsers
por: Cassel Darion, et al.
Publicado: (2022) -
Predicting heterogeneous ice nucleation with a data-driven approach
por: Martin Fitzner, et al.
Publicado: (2020) -
Investigating the utility of VR for spatial understanding in surgical planning: evaluation of head-mounted to desktop display
por: Georges Hattab, et al.
Publicado: (2021)