Background: Understanding living systems is crucial for curing diseases. To achieve this task we have to understand\nbiological networks based on protein-protein interactions. Bioinformatics has come up with a great amount of\ndatabases and tools that support analysts in exploring protein-protein interactions on an integrated level for\nknowledge discovery. They provide predictions and correlations, indicate possibilities for future experimental research\nand fill the gaps to complete the picture of biochemical processes. There are numerous and huge databases of\nprotein-protein interactions used to gain insights into answering some of the many questions of systems biology.\nMany computational resources integrate interaction data with additional information on molecular background.\nHowever, the vast number of diverse Bioinformatics resources poses an obstacle to the goal of understanding. We\npresent a survey of databases that enable the visual analysis of protein networks.\nResults: We selected M= 10 out of N= 53 resources supporting visualization, and we tested against the following\nset of criteria: interoperability, data integration, quantity of possible interactions, data visualization quality and data\ncoverage. The study reveals differences in usability, visualization features and quality as well as the quantity of\ninteractions. StringDB is the recommended first choice. CPDB presents a comprehensive dataset and IntAct lets the\nuser change the network layout. A comprehensive comparison table is available via web. The supplementary table\ncan be accessed on http://tinyurl.com/PPI-DB-Comparison-2015.\nConclusions: Only some web resources featuring graph visualization can be successfully applied to interactive visual\nanalysis of protein-protein interaction. Study results underline the necessity for further enhancements of visualization\nintegration in biochemical analysis tools. Identified challenges are data comprehensiveness, confidence, interactive\nfeature and visualization maturing.
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