Lucas Mikaël. (2022). How to use the TDCor algorithm to infer gene regulatory networks from time series transcriptomic data. In :
Lucas Mikaël (ed.). Plant systems biology : methods and protocols. New York : Springer, 13-31. (Methods in Molecular Biology ; 2395). ISBN 978-1-07-161814-1. ISSN 1064-3745.
Titre du document
How to use the TDCor algorithm to infer gene regulatory networks from time series transcriptomic data
Année de publication
2022
Type de document
Partie d'ouvrage
Auteurs
Lucas Mikaël
In
Lucas Mikaël (ed.)Plant systems biology : methods and protocols
Source
New York : Springer, 2022,
13-31 (Methods in Molecular Biology ; 2395). ISBN 978-1-07-161814-1 ISSN 1064-3745
Over the last few decades, many genes have been functionally characterized and shown to be involved in various metabolic, developmental, and signaling pathways. However 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. This is why unraveling the topology of gene regulatory networks (GRN) has become central to our understanding of all these processes. The recent advancement of high-throughput methods has provided enormous amount of -omics data. These data can now be exploited for rapid network reconstruction with statistical inference methods. We recently published a new GRN inference algorithm called TDCor which reconstructs GRN from time-series transcriptomic data. The algorithm has been released in the form of an R package. Here, I describe into details how to install and use the package.
Plan de classement
Biochimie [020BIOCHI]
;
Amélioration des plantes, ressources génétiques [076AMEPLA]
;
Mécanismes physiologique et biochimiques des plantes [076PHYBIO]
