Current Issue : July - September Volume : 2011 Issue Number : 3 Articles : 3 Articles
Parallel T-Coffee (PTC) was the first parallel implementation of the T-Coffee multiple sequence alignment tool. It is based on MPI and RMA mechanisms. Its purpose is to reduce the execution time of the large-scale sequence alignments. It can be run on distributed memory clusters allowing users to align data sets consisting of hundreds of proteins within a reasonable time. However, most of the potential users of this tool are not familiar with the use of grids or supercomputers.\nIn this paper we show how PTC can be easily deployed and controlled on a super computer architecture using a web portal developed using Rapid. Rapid is a tool for efficiently generating standardized portlets for a wide range of applications and the approach described here is generic enough to be applied to other applications, or to deploy PTC on different HPC environments.\nThe PTC portal allows users to upload a large number of sequences to be aligned by the parallel version of TC that cannot be aligned by a single machine due to memory and execution time constraints. The web portal provides a user-friendly solution....
Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS). However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface.\nTo urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80%) mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http://cloudaligner.sourceforge.net/ and its web version is at http://mine.cs.wayne.edu:8080/CloudAligner/.\nOur results show that CloudAligner is faster than CloudBurst, provides more accurate results than RMAP, and supports various input as well as output formats. In addition, with the web-based interface, it is easier to use than its counterparts....
With the rapid development and growth of the mobile industry, a considerable amount of mobile applications and services are available, which involve Internet scale data collections. Meanwhile, it has a tremendous impact on digital content providers as well as the mobile industry that a large number of digital content have been pirated and illegally distributed. Digital Rights Management (DRM) aims at protecting digital contents from being abused through regulating their usage. Unfortunately, to the best of our knowledge, fewer of these DRM schemes are concerned with the cost of the servers in a DRM system when the number of users scales up, and consider benefits of content providers who can be seen as tenants of a content server. In this paper, we propose CS-DRM, a cloud-based SIM DRM scheme, for the mobile Internet. The SIM card is introduced into CS-DRM to both reduce the cost and provide higher security. Also, the characteristics of cloud computing enable CS-DRM to bring benefits for content providers, and well satisfy the performance requirements with low cost when the number of users increases significantly. Furthermore, we have implemented a prototype of our DRM scheme, which demonstrates that CS-DRM is efficient, secure, and practicable....
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