| Corresponding with the development in technologies, the data produced by the biological studies, such as the Genomics, has been growing in an explosive style. This has challenged a lot to the analysis, the management and the integration of the data. The classical approaches, such as analyzing data manually or independently, have fallen far behind the increasing requirement of the data analysis. As a result, to develop large-scale, integrated and automated analyzing tools, has become a new hotspot, and a new trend in Bioinformatics studies.Meanwhile, with the rise of the Information Technologies, new technologies and applications have emerged like mushrooms in the network industry. The network is an ideal carrier for data interchanging and sharing. For the biological studies, the network was so important that, in the absence of networking, the researchers could hardly achieve anything from their work. The next-generation network technologies, such as Web2.0and Big Data Approaches, have been changing the network the way itself runs, the people the way we make use of it, as well as the Bioinformatics the future it will be. It is significant that, if or not can we take advantages of Web2.0and Big Data Approaches and apply them to the analysis and integration, will definitely decide our research efficiency and affect the balancing of the growing data and our processing ability.In this study, we started with the evolutionary analysis, successfully designed and implemented a Web2.0based comprehensive evolutionary analyzing toolkit EvoME. The name originated from the combination of "Evolution" and "Made Easy", meaning that "Evolutionary analysis made easy by EvoME".EvoME was written in Java and base on the GWT framework, and consisted of three fundamental functions: Ka/Ks calculation, Phylogenetic tree inference, and Visualization. Taking advantages of the interactive web technology AJAX, EvoME had integrated a series of programs including KaKs Calculator, ClustalW, PhyML, MEGA and BEAST, and added user-friendly wizard to them for a better user experience. In addition, EvoME had equipped with a phylogenetic tree viewer and annotation tool called EvolView, which was fully written from scratch. EvoME had implemented a good example of integrating and optimizing evolutionary analysis tools in the Web2.0framework.In this article, we resolved the design and the implementation of EvoME on the technical and application levels, in order to prove that, comparing with the formal web based toolkits, EvoME took prior on technology, design and integration. Meanwhile, with EvoME, we proved that the next-generation network technologies was applicable on Bioinformatics, and expected their new horizon of research and application.In the future, the EvoME will have more breakthroughs other than evolutionary analysis. As projected, EvoME will implement a general purpose workflow definition and controlling subsystem, which will allow users to assemble any programs to create their own analysis pipeline for their own purposes. Moreover, EvoME will have the ability to accelerate and analyze with Big Data Approaches. We hope that, with Big Data Approaches, more macro-scale suggestions and directions will be concluded from EvoME, thus providing us with more support on related studies. A beta demonstrative version of EvoME can be found at:http://www.evome.org... |
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