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researchprojects:researchjiayu [2016/11/15 13:55]
jiayu
researchprojects:researchjiayu [2016/11/15 14:15] (current)
jiayu
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 {{:​919edgar_apache.png?​nolink&​400 |}} {{:​919edgar_apache.png?​nolink&​400 |}}
  
-Because of the enormous advantage of NGS(next generation sequence) technologyresearchers now have the potential to analyze multiple genomes of several related bacterial strains ​at once to answer complex biological questions. EDGAR (Efficient Database framework for comparative Genome Analysis using BLAST score Ratios) is a software platform for bacterial genome analysis maintained by Justus-Liebig-University Giessen. It encloses all the NCBI publicly available bacterial genomes and uses statistical approach together with sequencing alignment to provide users othologous analysis. It also provides multiple comparative genomic visualization features. ​+NGS(next generation sequence) technology ​let researchers now have the potential to analyze multiple genomes of several related bacterial strains. EDGAR (Efficient Database framework for comparative Genome Analysis using BLAST score Ratios) is a software platform for bacterial genome analysis maintained by Justus-Liebig-University Giessen. It encloses all the NCBI publicly available bacterial genomes and uses statistical approach together with sequencing alignment to provide users othologous analysis. It also provides multiple comparative genomic visualization features. ​
  
 As NGS technology developing, more genomes are released and EDGAR itself met its processing bottleneck. In order to keep its popular features yet to have a high performance back-end, we proposed three improvable aspects. On the algorithmic level, we test and benchmark the available alignment algorithms and applications to eventually replace the conventional BLAST sequencing alignment. On the computational level, we use cutting edge parallel computation architecture to provide EDGAR a scalable, fault-tolerant and efficient infrastructure. On the database level, a NoSQL database model with its compatible data schema will be used to enhance the data I/O. As NGS technology developing, more genomes are released and EDGAR itself met its processing bottleneck. In order to keep its popular features yet to have a high performance back-end, we proposed three improvable aspects. On the algorithmic level, we test and benchmark the available alignment algorithms and applications to eventually replace the conventional BLAST sequencing alignment. On the computational level, we use cutting edge parallel computation architecture to provide EDGAR a scalable, fault-tolerant and efficient infrastructure. On the database level, a NoSQL database model with its compatible data schema will be used to enhance the data I/O.
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 The next step would be the database model change. Since we are inclined to utilize a NoSQL database, the current MySQL data schema of EDGAR will be re-designed. The next step would be the database model change. Since we are inclined to utilize a NoSQL database, the current MySQL data schema of EDGAR will be re-designed.
  
-//​Supervisors:​ Alexander Goesmann (Bielefeld ​University),​ Alexander Sczyrba (Bielefeld University)//​+//​Supervisors:​ Alexander Goesmann (Justus Liebig ​University ​Giessen), Alexander Sczyrba (Bielefeld ​University),​ Fiona Brinkman (Simon Fraser ​University)//​
researchprojects/researchjiayu.1479218154.txt.gz · Last modified: 2016/11/15 13:55 by jiayu