Cargando…
HCGA: Highly comparative graph analysis for network phenotyping
Networks are widely used as mathematical models of complex systems across many scientific disciplines. Decades of work have produced a vast corpus of research characterizing the topological, combinatorial, statistical, and spectral properties of graphs. Each graph property can be thought of as a fea...
Autores principales: | Peach, Robert L., Arnaudon, Alexis, Schmidt, Julia A., Palasciano, Henry A., Bernier, Nathan R., Jelfs, Kim E., Yaliraki, Sophia N., Barahona, Mauricio |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085611/ https://www.ncbi.nlm.nih.gov/pubmed/33982022 http://dx.doi.org/10.1016/j.patter.2021.100227 |
Ejemplares similares
-
Relative, local and global dimension in complex networks
por: Peach, Robert, et al.
Publicado: (2022) -
From free text to clusters of content in health records: an unsupervised graph partitioning approach
por: Altuncu, M. Tarik, et al.
Publicado: (2019) -
Data-driven unsupervised clustering of online learner behaviour
por: Peach, Robert L., et al.
Publicado: (2019) -
Sensitivity and spectral control of network lasers
por: Saxena, Dhruv, et al.
Publicado: (2022) -
ProteinLens: a web-based application for the analysis of allosteric signalling on atomistic graphs of biomolecules
por: Mersmann, Sophia F, et al.
Publicado: (2021)