Title |
A web-based protein interaction network visualizer
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Published in |
BMC Bioinformatics, May 2014
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DOI | 10.1186/1471-2105-15-129 |
Pubmed ID | |
Authors |
Gustavo A Salazar, Ayton Meintjes, Gaston K Mazandu, Holifidy A Rapanoël, Richard O Akinola, Nicola J Mulder |
Abstract |
Interaction between proteins is one of the most important mechanisms in the execution of cellular functions. The study of these interactions has provided insight into the functioning of an organism's processes. As of October 2013, Homo sapiens had over 170000 Protein-Protein interactions (PPI) registered in the Interologous Interaction Database, which is only one of the many public resources where protein interactions can be accessed. These numbers exemplify the volume of data that research on the topic has generated. Visualization of large data sets is a well known strategy to make sense of information, and protein interaction data is no exception. There are several tools that allow the exploration of this data, providing different methods to visualize protein network interactions. However, there is still no native web tool that allows this data to be explored interactively online. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Italy | 1 | 11% |
Colombia | 1 | 11% |
Spain | 1 | 11% |
Australia | 1 | 11% |
Norway | 1 | 11% |
Unknown | 4 | 44% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 6 | 67% |
Scientists | 2 | 22% |
Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 3 | 4% |
Germany | 2 | 3% |
Australia | 1 | 1% |
Netherlands | 1 | 1% |
Canada | 1 | 1% |
Argentina | 1 | 1% |
Nigeria | 1 | 1% |
Japan | 1 | 1% |
United States | 1 | 1% |
Other | 0 | 0% |
Unknown | 57 | 83% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 18 | 26% |
Student > Master | 14 | 20% |
Student > Ph. D. Student | 13 | 19% |
Student > Bachelor | 9 | 13% |
Student > Doctoral Student | 3 | 4% |
Other | 8 | 12% |
Unknown | 4 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 29 | 42% |
Biochemistry, Genetics and Molecular Biology | 15 | 22% |
Computer Science | 14 | 20% |
Arts and Humanities | 3 | 4% |
Nursing and Health Professions | 1 | 1% |
Other | 3 | 4% |
Unknown | 4 | 6% |