- Erratum
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- Published:
Erratum to: ppiPre: predicting protein-protein interactions by combining heterogeneous features
BMC Systems Biology volume 9, Article number: 50 (2015)
The original article was published in BMC Systems Biology 2013 7:S8
Erratum
The authors wish to acknowledge that the software package associated with our Research Article [1], under the name ‘ppiPre’, re-used software code for some of its functions from an existing software package, GOSemSim [2], without proper attribution and in breach of the software’s licencing terms. Additionally we neglected to cite the article by Yu et al. [3] describing the GoSemSim software.
The software code from GoSemSim [2] is used in the implementation of two GO semantic similarity measures, TCSS and IntelliGO. ppiPre additionally implements a KEGG-based similarity measure and three topological similarity measures, and integrates features with a support vector machine.
We have now updated our software package such that it is licensed under a compatible GPL version 2 licence, and revised the package to give the appropriate attribution.
We apologize for any inconvenience this oversight may have caused.
Availability and Requirements
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Project name: ppiPre.
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Project home page: http://cran.r-project.org/web/packages/ppiPre/index.html.
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Operating system(s): Platform independent.
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Programming language: R.
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Other requirements: None.
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License: GPL-2.
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Any restrictions to use by non-academics: None.
References
- 1.
Yue D, Lin G, Bingbo W. ppiPre: predicting protein-protein interactions by combining heterogeneous features. BMC Syst Biol. 2013;7 Suppl 2:S8.
- 2.
Guangchuang Yu. GOSemSim. http://www.bioconductor.org/packages/release/bioc/html/GOSemSim.html. (Accessed 7 July 2015)
- 3.
Yu G, Li F, Qin Y, Bo X, Wu Y, Wang S. GOSemSim: an R package for measuring semantic similarity among GO terms and gene products. Bioinformatics. 2010;26:976–8.
Author information
Additional information
The online version of the original article can be found under doi:10.1186/1752-0509-7-S2-S8.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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