c(person(given = "Shilin",
family = "Ouyang",
role = c("aut", "cre"),
email = "ouyangshilin@hnu.edu.cn"),
person(given = "Zihao",
family = "Li",
role = "aut"),
person(given = "Jiamin",
family = "Hu",
role = "aut"),
person(given = "Miyuan",
family = "Cao",
role = "aut"),
person(given = "Feng",
family = "Yu",
role = "aut"),
person(given = "Longfei",
family = "Mao",
role = "aut"),
person("RStudio",
role = c("cph", "fnd")))
Visualize the steps, transformation information, databases used in a metabolic reconstruction,
by inputting an article in the form of txt.
ape, dplyr, ggplot2, ggtree, methods, patchwork, plyr,
RColorBrewer, readr, readxl, rlang, SnowballC, stats, stringr,
tidyverse, tm
Shilin Ouyang [aut, cre],
Zihao Li [aut],
Jiamin Hu [aut],
Miyuan Cao [aut],
Feng Yu [aut],
Longfei Mao [aut],
RStudio [cph, fnd]

The tool that quantitatively and qualitatively specifies each reconstruction steps
and can generate a template list of reconstruction steps dynamically selected from a reconstruction step reservoir,
constructed based on all available published GSM papers.

In the past decade, genome-scale metabolic reconstructions have widely been
used to comprehend the systems biology of metabolic pathways within an organism.
Different GSMs are constructed using various techniques that
require distinct steps, but the input data, information conversion and software tools
are neither concisely defined nor mathematically or programmatically formulated
in a context-specific manner.The tool that quantitatively and qualitatively specifies
each reconstruction steps and can generate a template list of reconstruction steps dynamically
selected from a reconstruction step reservoir, constructed based on all available published papers.

person("Jean-Baptiste", "Hasse", email = "jb-hasse@hotmail.fr", role = c("aut", "cre"))
The past decade has demonstrated an increased need to better understand risks leading to systemic crises. This framework offers scholars, practitioners and policymakers a useful toolbox to explore such risks in financial systems. Specifically, this framework provides popular econometric and network measures to monitor systemic risk and to measure the consequences of regulatory decisions. These systemic risk measures are based on the frameworks of Adrian and Brunnermeier (2016) <doi:10.1257/aer.20120555> and Billio, Getmansky, Lo and Pelizzon (2012) <doi:10.1016/j.jfineco.2011.12.010>.