Author: Alex T. Kalinka <alex.t.kalinka@gmail.com>, with contributions from Alain Guenoche
Description: Link communities reveal the nested and overlapping structure in networks, and uncover the key nodes that form connections to multiple communities. linkcomm provides a set of tools for generating, visualizing, and analysing link communities in networks of arbitrary size and type. The linkcomm package also includes tools for generating, visualizing, and analysing Overlapping Cluster Generator (OCG) communities.

Packaged: 2020-03-11 20:31:28 UTC; alexkalinka

Author: Alex T. Kalinka <alex.t.kalinka@gmail.com>, with
structure in networks, and uncover the key nodes that form connections
to multiple communities. linkcomm provides a set of tools for
generating, visualizing, and analysing link communities in networks of
arbitrary size and type. The linkcomm package also includes tools for
generating, visualizing, and analysing Overlapping Cluster Generator
(OCG) communities. Kalinka and Tomancak (2011) <10.1093/bioinformatics/btr311>.
Packaged: 2020-10-05 20:51:52 UTC; alexkalinka

(OCG) communities. Kalinka and Tomancak (2011) <doi:10.1093/bioinformatics/btr311>.
Packaged: 2021-02-04 15:54:52 UTC; alexkalinka

Author: Alex T. Kalinka <alex.t.kalinka@gmail.com>, with contributions
communities in networks of arbitrary size and type. The
linkcomm package also includes tools for generating,
visualizing, and analysing Overlapping Cluster Generator (OCG)

Title: Access to 'LinkedIn' Ads via the 'Windsor.ai' API
Description: Collect  marketing data from 'LinkedIn' Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

Title: Linkage information based genotype imputation method
Author: Yi Xu <statxy@gmail.com> and Jixiang Wu <jixiang.wu@sdstate.edu>
Description: A linkage information based method for imputing missing diploid genotypes

person( "Michal", "Bojanowski", email="michal2992@gmail.com", role=c("aut", "cre")),
person(family="National Science Centre", role="fnd", comment="grant 2012/07/D/HS6/01971")
Description: Implementations of most of the existing proximity-based methods of
link prediction in graphs. Among the 20 implemented methods are e.g.:
Fouss F., Pirotte A., Renders J., and Saerens M. (2007) <doi:10.1109/TKDE.2007.46>.
Packaged: 2018-10-12 14:38:02 UTC; mbojanowski
National Science Centre [fnd] (grant 2012/07/D/HS6/01971)