Chapter title |
Bioinformatics Analysis of Protein Secretion in Plants
|
---|---|
Chapter number | 3 |
Book title |
Plant Protein Secretion
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-7262-3_3 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7261-6, 978-1-4939-7262-3
|
Authors |
Liyuan Chen |
Abstract |
In sessile plants, the dynamic protein secretion pathways orchestrate the cellular responses to internal signals and external environmental changes in almost every aspect of plant developmental events. The cohort of plant proteins, secreted from the plant cells into the extracellular matrix, has been annotated as plant secretome. Therefore, the identification and characterization of secreted proteins will discover novel secretory potentials and establish the functional connection between cellular protein secretion and plant physiological phenomena. Noteworthy, an increasing number of bioinformatics databases and tools have been developed for computational predictions on either secreted proteins or secretory pathways. This chapter summarizes current accessible databases and tools for protein secretion analysis in Arabidopsis thaliana and higher plants, and provides feasible methodologies for bioinformatics analysis of secretome studies for the plant research community. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 3 | 23% |
Student > Master | 2 | 15% |
Researcher | 2 | 15% |
Student > Ph. D. Student | 1 | 8% |
Professor | 1 | 8% |
Other | 1 | 8% |
Unknown | 3 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 3 | 23% |
Biochemistry, Genetics and Molecular Biology | 3 | 23% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
Business, Management and Accounting | 1 | 8% |
Engineering | 1 | 8% |
Other | 0 | 0% |
Unknown | 4 | 31% |