Title |
NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference
|
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Published in |
BMC Bioinformatics, September 2015
|
DOI | 10.1186/s12859-015-0728-4 |
Pubmed ID | |
Authors |
Pau Bellot, Catharina Olsen, Philippe Salembier, Albert Oliveras-Vergés, Patrick E. Meyer |
Abstract |
In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods. Our open-source and freely available Bioconductor package aggregates a large set of tools to assess the robustness of network inference algorithms against different simulators, topologies, sample sizes and noise intensities. The benchmarking framework that uses various datasets highlights the specialization of some methods toward network types and data. As a result, it is possible to identify the techniques that have broad overall performances. |
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Spain | 3 | 33% |
United States | 1 | 11% |
Italy | 1 | 11% |
Unknown | 4 | 44% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 56% |
Scientists | 4 | 44% |
Mendeley readers
Geographical breakdown
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India | 1 | 1% |
Sri Lanka | 1 | 1% |
Australia | 1 | 1% |
Unknown | 86 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 22 | 25% |
Student > Ph. D. Student | 17 | 19% |
Student > Master | 11 | 12% |
Student > Bachelor | 8 | 9% |
Student > Doctoral Student | 6 | 7% |
Other | 14 | 16% |
Unknown | 11 | 12% |
Readers by discipline | Count | As % |
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Computer Science | 20 | 22% |
Agricultural and Biological Sciences | 18 | 20% |
Biochemistry, Genetics and Molecular Biology | 17 | 19% |
Engineering | 9 | 10% |
Mathematics | 5 | 6% |
Other | 9 | 10% |
Unknown | 11 | 12% |