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Mendeley readers
Chapter title |
Databases and Computational Tools for Evolutionary Analysis of Protein Phosphorylation
|
---|---|
Chapter number | 29 |
Book title |
Kinase Signaling Networks
|
Published in |
Methods in molecular biology, July 2017
|
DOI | 10.1007/978-1-4939-7154-1_29 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7152-7, 978-1-4939-7154-1
|
Authors |
Chris Soon Heng Tan |
Abstract |
Advancements in MS-based phospho-proteomics techniques have helped uncover hundred thousands of protein phosphorylation sites in human and various model organisms. The majority of these sites are uncharacterized. The sheer number of uncharacterized sites necessitates systematic approaches to prioritize sites for more in-depth annotation. Analyzing the phosphorylation and sequence conservation of uncharacterized sites across species can help reveal a subset of the functionally important phosphorylation events. Here, we outline the workflow and provide an overview of publicly available computational resources for conservation analysis of novel phosphorylation sites. |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 6 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 2 | 33% |
Student > Ph. D. Student | 1 | 17% |
Other | 1 | 17% |
Researcher | 1 | 17% |
Professor > Associate Professor | 1 | 17% |
Other | 0 | 0% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 2 | 33% |
Biochemistry, Genetics and Molecular Biology | 1 | 17% |
Agricultural and Biological Sciences | 1 | 17% |
Chemistry | 1 | 17% |
Unknown | 1 | 17% |