@incollection{fdi:010084048,
  title = {{H}ow to use the {TDC}or algorithm to infer gene regulatory networks from time series transcriptomic data},
  author = {{L}ucas, {M}ika{\¨e}l},
  editor = {},
  language = {{ENG}},
  abstract = {{O}ver the last few decades, many genes have been functionally characterized and shown to be involved in various metabolic, developmental, and signaling pathways. {H}owever it still remains unclear how all these genes and pathways integrate into a unique regulatory network to coordinate the development and the growth, or the response to the environment. {T}his is why unraveling the topology of gene regulatory networks ({GRN}) has become central to our understanding of all these processes. {T}he recent advancement of high-throughput methods has provided enormous amount of -omics data. {T}hese data can now be exploited for rapid network reconstruction with statistical inference methods. {W}e recently published a new {GRN} inference algorithm called {TDC}or which reconstructs {GRN} from time-series transcriptomic data. {T}he algorithm has been released in the form of an {R} package. {H}ere, {I} describe into details how to install and use the package.},
  keywords = {},
  booktitle = {{P}lant systems biology : methods and protocols},
  numero = {2395},
  pages = {13--31},
  address = {{N}ew {Y}ork},
  publisher = {{S}pringer},
  series = {{M}ethods in {M}olecular {B}iology},
  year = {2022},
  DOI = {10.1007/978-1-0716-1816-5_2},
  ISBN = {978-1-07-161814-1},
  ISSN = {1064-3745},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084048},
}