Chapter title |
A Systems Biology Methodology Combining Transcriptome and Interactome Datasets to Assess the Implications of Cytokinin Signaling for Plant Immune Networks
|
---|---|
Chapter number | 14 |
Book title |
Auxins and Cytokinins in Plant Biology
|
Published in |
Methods in molecular biology, March 2017
|
DOI | 10.1007/978-1-4939-6831-2_14 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6829-9, 978-1-4939-6831-2
|
Authors |
Kunz, Meik, Dandekar, Thomas, Naseem, Muhammad, Meik Kunz, Thomas Dandekar, Muhammad Naseem |
Editors |
Thomas Dandekar, Muhammad Naseem |
Abstract |
Cytokinins (CKs) play an important role in plant growth and development. Also, several studies highlight the modulatory implications of CKs for plant-pathogen interaction. However, the underlying mechanisms of CK mediating immune networks in plants are still not fully understood. A detailed analysis of high-throughput transcriptome (RNA-Seq and microarrays) datasets under modulated conditions of plant CKs and its mergence with cellular interactome (large-scale protein-protein interaction data) has the potential to unlock the contribution of CKs to plant defense. Here, we specifically describe a detailed systems biology methodology pertinent to the acquisition and analysis of various omics datasets that delineate the role of plant CKs in impacting immune pathways in Arabidopsis. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 5 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 1 | 20% |
Professor > Associate Professor | 1 | 20% |
Researcher | 1 | 20% |
Student > Master | 1 | 20% |
Unknown | 1 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 3 | 60% |
Biochemistry, Genetics and Molecular Biology | 1 | 20% |
Unknown | 1 | 20% |