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Inferring gene regulatory networks using Kendall’s tau correlation coefficient and identification of salinity stress responsive genes in rice

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Title Inferring gene regulatory networks using Kendall’s tau correlation coefficient and identification of salinity stress responsive genes in rice
Not Available
 
Creator Samarendra Das
Prabina Kumar Meher
Upendra Kumar Pradhan
Amrit Kumar Paul
 
Subject Correlation coefficient
gene regulatory networks
rice
salinity
 
Description Not Available
Salinity is one of the most common abiotic stresses
that limit the production of rice. Since salinity stress
tolerance is controlled by many genes, identification of
these stress responsive genes as well as to understand
the underlying mechanisms is of importance from
breeding point of view. In this direction, the reverse
engineering of gene regulatory networks has proven to
be successful. In this study, we construct the gene
regulatory network using Kendall’s tau correlation
coefficient, in order to identify the stress responsive
genes. The proposed approach was tested on a rice
microarray dataset and 18 key genes were identified.
Most of these key genes were found to be involved
directly or indirectly in salinity stress, as evidenced
from the published literature. Gene ontology analysis
further confirmed the involvement of the selected
genes in ion binding, oxidation-reduction and phosphorylation activities. These identified genes can be
targeted for breeding salt-tolerant varieties of rice.
Not Available
 
Date 2022-08-07T06:52:15Z
2022-08-07T06:52:15Z
2017-03-25
 
Type Research Paper
 
Identifier Samarendra Das, Prabina Kumar Meher, Upendra Kumar Pradhan and Amrit Kumar Paul (2017). Inferring gene regulatory networks using Kendall’s tau correlation coefficient and identification of salinity stress responsive genes in rice, Research Communication, 112(6), 1257-62.
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/73735
 
Language English
 
Relation Not Available;
 
Publisher Not Available