Title |
Cluster based prediction of PDZ-peptide interactions
|
---|---|
Published in |
BMC Genomics, January 2014
|
DOI | 10.1186/1471-2164-15-s1-s5 |
Pubmed ID | |
Authors |
Kousik Kundu, Rolf Backofen |
Abstract |
PDZ domains are one of the most promiscuous protein recognition modules that bind with short linear peptides and play an important role in cellular signaling. Recently, few high-throughput techniques (e.g. protein microarray screen, phage display) have been applied to determine in-vitro binding specificity of PDZ domains. Currently, many computational methods are available to predict PDZ-peptide interactions but they often provide domain specific models and/or have a limited domain coverage. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 3 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 1 | 2% |
Unknown | 40 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 13 | 32% |
Researcher | 9 | 22% |
Student > Bachelor | 3 | 7% |
Student > Doctoral Student | 3 | 7% |
Professor > Associate Professor | 3 | 7% |
Other | 5 | 12% |
Unknown | 5 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 15 | 37% |
Agricultural and Biological Sciences | 8 | 20% |
Computer Science | 3 | 7% |
Chemistry | 3 | 7% |
Engineering | 2 | 5% |
Other | 4 | 10% |
Unknown | 6 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 November 2014.
All research outputs
#17,286,379
of 25,374,917 outputs
Outputs from BMC Genomics
#7,120
of 11,244 outputs
Outputs of similar age
#202,469
of 320,961 outputs
Outputs of similar age from BMC Genomics
#126
of 204 outputs
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