Title: Rapid Reconstruction of Time-Varying Gene Regulatory Networks
Authors@R: c(person("Manan", "Gupta", , "guptamanan100@gmail.com", c("aut", "cre")),person("Saptarshi", "Pyne", ,"saptarshipyne01@gmail.com", role = "aut"),person("Alok", "Kumar", ,"alok4039@gmail.com", role = "aut"),   person("Ashish", "Anand", , "anand.ashish@iitg.ac.in", role = "aut"))
Description: Rapid advancement in high-throughput gene expression measurement technologies has resulted in genome- scale time series datasets. Uncovering the underlying temporal sequence of gene regulatory events in the form of time-varying Gene Regulatory Networks (GRNs) demands computationally fast, accurate and highly scalable algorithms. To provide a flexible framework in a significantly time-efficient manner, a novel algorithm, namely TGS (Ashish Anand et al., 2018 <doi:10.1109/TCBB.2018.2861698>), is proposed here. TGS is shown to consume only 29 minutes for a microarray dataset with 4028 genes. Moreover, it provides the flexibility and time-efficiency, without losing the accuracy. Nevertheless, TGS’s main memory requirement grows exponentially with the number of genes, which it tackles by restricting the maximum number of regulators for each gene. Relaxing this restriction remains an important challenge as the true number of regulators is not known a prior.
Imports: minet, stats, base, utils, bnstruct, ggm, foreach, doParallel,

Description: Rapid advancements in high-throughput gene sequencing
technologies have resulted in genome-scale time-series datasets.
Uncovering the underlying temporal sequence of gene regulatory events
in the form of time-varying gene regulatory networks demands
accurate and computationally efficient algorithms. Such an
algorithm is 'TGS'. It is proposed in Saptarshi Pyne, Alok Ranjan
Kumar, and Ashish Anand. Rapid reconstruction of time-varying
gene regulatory networks. IEEE/ACM Transactions on Computational
Biology and Bioinformatics, 17(1):278{291, Jan-Feb 2020. The TGS
algorithm is shown to consume only 29 minutes for a microarray
dataset with 4028 genes. This package provides an implementation
person(given = "Saptarshi", family = "Pyne", email = "saptarshipyne01@gmail.com", role = c("aut", "cre"),
person(given = "Manan", family = "Gupta", email = "guptamanan100@gmail.com", role = "aut"),
person(given = "Alok", family = "Kumar", email = "alok4039@gmail.com", role = "aut"),
person(given = "Ashish", family = "Anand", email = "anand.ashish@iitg.ac.in", role = "aut",
biocViews: NetworkInference, GraphAndNetwork, Network, GeneExpression,
Imports: rjson, bnstruct, ggm, foreach, doParallel, minet (>= 3.38.0)
Suggests: R.rsp, testthat (>= 2.1.0), knitr, rmarkdown
Author: Saptarshi Pyne [aut, cre] (<https://orcid.org/0000-0001-9710-6749>),