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2015 ; 16
(1
): 195
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Integrated web visualizations for protein-protein interaction databases
#MMPMID26077899
Jeanquartier F
; Jean-Quartier C
; Holzinger A
BMC Bioinformatics
2015[Jun]; 16
(1
): 195
PMID26077899
show ga
BACKGROUND: Understanding living systems is crucial for curing diseases. To
achieve this task we have to understand biological networks based on
protein-protein interactions. Bioinformatics has come up with a great amount of
databases and tools that support analysts in exploring protein-protein
interactions on an integrated level for knowledge discovery. They provide
predictions and correlations, indicate possibilities for future experimental
research and fill the gaps to complete the picture of biochemical processes.
There are numerous and huge databases of protein-protein interactions used to
gain insights into answering some of the many questions of systems biology. Many
computational resources integrate interaction data with additional information on
molecular background. However, the vast number of diverse Bioinformatics
resources poses an obstacle to the goal of understanding. We present a survey of
databases that enable the visual analysis of protein networks. RESULTS: We
selected M=10 out of N=53 resources supporting visualization, and we tested
against the following set of criteria: interoperability, data integration,
quantity of possible interactions, data visualization quality and data coverage.
The study reveals differences in usability, visualization features and quality as
well as the quantity of interactions. StringDB is the recommended first choice.
CPDB presents a comprehensive dataset and IntAct lets the user change the network
layout. A comprehensive comparison table is available via web. The supplementary
table can be accessed on http://tinyurl.com/PPI-DB-Comparison-2015. CONCLUSIONS:
Only some web resources featuring graph visualization can be successfully applied
to interactive visual analysis of protein-protein interaction. Study results
underline the necessity for further enhancements of visualization integration in
biochemical analysis tools. Identified challenges are data comprehensiveness,
confidence, interactive feature and visualization maturing.
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