c(
person("Ryan", "Elmore", email = "Ryan.Elmore@du.edu", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-0092-4532")),
person("Ben", "Williams", email = "Benjamin.Williams@du.edu", role = "aut", comment = c(ORCID = "0000-0001-8474-5066")),
person("Will", "Palmquist", email = "Will.Palmquist@du.edu", role = "aut", comment = c(ORCID = "0000-0002-6100-0923")))
The intent here is to enable the simulation of plays/drives and
evaluate game-play strategies in the National Football League (NFL).
Built-in strategies include going for it on fourth down and varying the
proportion of passing/rushing plays during a drive. The user should be
familiar with nflscrapR data before trying to write his/her own
strategies. This work is inspired by a blog post by Mike Lopez,
currently the  Director of Data and Analytics at the NFL, Lopez (2019) <https://statsbylopez.netlify.app/post/resampling-nfl-drives/>.

An implementation of the network fingerprint framework. This method
worked by making systematic comparisons to a set of well-studied "basic networks",
measuring both the functional and topological similarity.  A biological could be
characterized as a spectrum-like vector consisting of similarities to basic
networks. It shows great potential in biological network study.
igraph, stringr, magrittr, plyr, ggplot2, apcluster,
KEGGgraph, dplyr, tidyr, methods
knitr, testthat, BiocStyle, graphite, NFPdata

c(
person("Yang", "Cao",email = "yiluheihei@gmail.com",role = c("aut","cre" )),
person("Fei", "Li", email = "pittacus@gmail.com", role = "aut")
)
An implementation of the network fingerprint framework that introduced
in paper "Network fingerprint: a knowledge-based characterization of biomedical
networks" (Cui, 2015) <doi:10.1038/srep13286>. This method worked by making
systematic comparisons to a set of well-studied "basic networks", measuring
both the functional and topological similarity.  A biological could be
characterized as a spectrum-like vector consisting of similarities to basic
networks. It shows great potential in biological network study.