GRAPH Interaction from pathway Topological Environment
Gabriele Sales <gabriele.sales@unipd.it>, Enrica Calura
<enrica.calura@gmail.com>, Chiara Romualdi
<chiara.romualdi@unipd.it>
Graph objects from pathway topology derived from NCI,
KEGG, Biocarta and Reactome databases.

R (>= 2.10), methods, graph, AnnotationDbi, org.Hs.eg.db
DEGraph (>= 1.4), hgu133plus2.db, RCytoscape (>= 1.2), SPIA
(>= 2.2), topologyGSA (>= 1.0)

A fast C++ implementation of various graph kernels.

A fast C++ implementation for computing various graph kernels including (1) simple kernels between vertex and/or edge label histograms, (2) random walk kernels (popular baselines), and (3) the Weisfeiler-Lehman graph kernel (state-of-the-art).

A fast C++ implementation for computing various graph kernels including (1) simple kernels between vertex and/or edge label histograms, (2) graphlet kernels, (3) random walk kernels (popular baselines), and (4) the Weisfeiler-Lehman graph kernel (state-of-the-art).

c(person(given = "Mahito",
family = "Sugiyama",
email = "mahito@nii.ac.jp",
role = c("aut", "cre")),
person(given = "The development of the graphkernels open access software package was financially supported by the Horizon 2020/CDS-QUAMRI/634541 project. This support is gratefully acknowledged.",
role = "fnd"))
Mahito Sugiyama [aut, cre],
The development of the graphkernels open access software package was
financially supported by the Horizon 2020/CDS-QUAMRI/634541
project. This support is gratefully acknowledged. [fnd]

Additional Layout Algorithms for Network Visualizations
person("David", "Schoch", email = "david.schoch@manchester.ac.uk", role = c("aut", "cre"))
Several new layout algorithms to visualize networks are provided which are not part of 'igraph'.
Most are based on the concept of stress majorization by Gansner et al. (2004) <doi:10.1007/978-3-540-31843-9_25>.
Some more specific algorithms allow to emphasize hidden group structures in networks or focus on specific nodes.
testthat, ggraph, ggplot2, knitr, rmarkdown