Abstract
Methods for detecting protein complexes from protein-protein interaction networks are of the most critical computational approaches. Numerous methods have been proposed in this area. Therefore, it is necessary to evaluate them. Various metrics have been proposed in order to compare these methods. Nevertheless, it is essential to define new metrics that evaluate methods both qualitatively and quantitatively. In addition, there is no tool for the comprehensive comparison of such methods. In this paper, a new criterion is introduced that can fully evaluate protein complex detection algorithms. We introduce CDAP (Complex Detection Analyzer Package); an online package for comparing protein complex detection methods. CDAP can quickly rank the performance of methods based on previously defined as well as newly introduced criteria in various settings (4 PPI datasets and 3 gold standards). It has the capability of integrating various methods and apply several filterings on the results. CDAP can be easily extended to include new datasets, gold standards, and methods. Furthermore, the user can compare the results of a custom method with the results of existing methods. Thus, the authors of future papers can use CDAP for comparing their method with the previous ones. A case study is done on YGR198W, a well-known protein, and the detected clusters are compared to the known complexes of this protein.
Highlights
Methods for detecting protein complexes from protein-protein interaction networks (PPINs) are of the most critical computational methods which have been widely used recently
For a specified evaluation metric and the specified value of the threshold, method A may be better than method B; while with a different value of the threshold and the same criterion, method B is better than method A
Many evaluation metrics have been proposed previously such as ACC, positive predictive value (PPV), SN, Precision, Recall, F – measure, PrecisionN, RecallN, and MMR, each of which has some drawbacks and cannot fully reflect the quality of an algorithm
Summary
Methods for detecting protein complexes from protein-protein interaction networks (PPINs) are of the most critical computational methods which have been widely used recently. Several methods have been proposed for the discovery of protein-protein interactions in recent years[4] By using these methods, very large networks of interactions between proteins can be created which are a suitable bed for complex detection methods. Very large networks of interactions between proteins can be created which are a suitable bed for complex detection methods These networks are commonly known as PPI networks and can be modeled by weighted graphs; so that each vertex represents a protein and each interaction between two proteins is represented by a weighted edge between the corresponding nodes. The difference in the amount of reliability can be modeled by the weight of the associated edge in the mentioned graph[5]
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