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  • Erratum
  • Open Access

Erratum to: ppiPre: predicting protein-protein interactions by combining heterogeneous features

BMC Systems Biology20159:50

  • Received: 13 August 2015
  • Accepted: 13 August 2015
  • Published:

The original article was published in BMC Systems Biology 2013 7:S8


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



Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, 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 ( applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

School of Computer Science and Technology, Xidian University, Xi’an, 710071, PR China
Institute of Software Engineering, Xidian University, Xi’an, 710071, PR China


  1. Yue D, Lin G, Bingbo W. ppiPre: predicting protein-protein interactions by combining heterogeneous features. BMC Syst Biol. 2013;7 Suppl 2:S8.View ArticleGoogle Scholar
  2. Guangchuang Yu. GOSemSim. (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.View ArticlePubMedGoogle Scholar


© Deng et al. 2015