Title |
eXamine: Exploring annotated modules in networks
|
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Published in |
BMC Bioinformatics, July 2014
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DOI | 10.1186/1471-2105-15-201 |
Pubmed ID | |
Authors |
Kasper Dinkla, Mohammed El-Kebir, Cristina-Iulia Bucur, Marco Siderius, Martine J Smit, Michel A Westenberg, Gunnar W Klau |
Abstract |
Biological networks have a growing importance for the interpretation of high-throughput "omics" data. Integrative network analysis makes use of statistical and combinatorial methods to extract smaller subnetwork modules, and performs enrichment analysis to annotate the modules with ontology terms or other available knowledge. This process results in an annotated module, which retains the original network structure and includes enrichment information as a set system. A major bottleneck is a lack of tools that allow exploring both network structure of extracted modules and its annotations. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 40% |
Spain | 2 | 20% |
Germany | 1 | 10% |
Switzerland | 1 | 10% |
Netherlands | 1 | 10% |
Unknown | 1 | 10% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 6 | 60% |
Members of the public | 4 | 40% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 2 | 3% |
United Kingdom | 2 | 3% |
United States | 2 | 3% |
Germany | 1 | 2% |
Brazil | 1 | 2% |
France | 1 | 2% |
Norway | 1 | 2% |
Luxembourg | 1 | 2% |
Unknown | 51 | 82% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 20 | 32% |
Student > Ph. D. Student | 18 | 29% |
Student > Master | 5 | 8% |
Student > Bachelor | 3 | 5% |
Other | 3 | 5% |
Other | 8 | 13% |
Unknown | 5 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 27% |
Computer Science | 14 | 23% |
Biochemistry, Genetics and Molecular Biology | 9 | 15% |
Engineering | 4 | 6% |
Mathematics | 3 | 5% |
Other | 8 | 13% |
Unknown | 7 | 11% |