Selection of organisms for the co-evolution-based study of protein interactions

BMC Bioinformatics

Research Article

Florencio Pazos¹  David Ochoa¹  Daniel Lopez¹  Dorota Herman²  Alfonso Valencia³  David Juan³ 

[1] Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain;Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain;Centre for Systems Biology (CSB), School of Biosciences, University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK;Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernández Almagro 3, 28029, Madrid, Spain;

关键词: Receiver Operating Characteristic Curve;    Macromolecular Complex;    Phylogenetic Profile;    Transient Interaction;    Receiver Operating Characteristic Plot;   

DOI  :  10.1186/1471-2105-12-363

 received in 2011-03-11, accepted in 2011-09-12,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundThe prediction and study of protein interactions and functional relationships based on similarity of phylogenetic trees, exemplified by the mirrortree and related methodologies, is being widely used. Although dependence between the performance of these methods and the set of organisms used to build the trees was suspected, so far nobody assessed it in an exhaustive way, and, in general, previous works used as many organisms as possible. In this work we asses the effect of using different sets of organism (chosen according with various phylogenetic criteria) on the performance of this methodology in detecting protein interactions of different nature.ResultsWe show that the performance of three mirrortree-related methodologies depends on the set of organisms used for building the trees, and it is not always directly related to the number of organisms in a simple way. Certain subsets of organisms seem to be more suitable for the predictions of certain types of interactions. This relationship between type of interaction and optimal set of organism for detecting them makes sense in the light of the phylogenetic distribution of the organisms and the nature of the interactions.ConclusionsIn order to obtain an optimal performance when predicting protein interactions, it is recommended to use different sets of organisms depending on the available computational resources and data, as well as the type of interactions of interest.

【 授权许可】

Unknown   
© Herman et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.