ABSTRACT
With the rapid development of biotechnology such as NGS and proteomics , bioinformatics has seen an explo-sion in diversity and complexity in terms of data , tools and demands .The traditional computing environment , including ded-icated workstations and virtual machines , are no longer suitable under such circumstances .As a rising container technolo-gy, Docker, which is characterized by light weight , openness and security ,has provided an innovative solution to analysis and processing of biological big data and attracted increasing attention from bioinformatics developers and users .Consider-ing the demands and features of development , deployment and application of bioinformatics tools in the age of big data , this paper analyzes the advantages of Docker in this field , introduces some actual cases and discusses current deficiencies and future improvement .
ABSTRACT
The development of high throughput sequencing technology has promoted the development of many related spheres of research .Many research institutions are studying algorithms of microorganism detection using high throughput se -quencing data .Some algorithms have already been designed and published .In this paper , we investigated the literature re-garding the use of high throughput sequencing data for microorganism detection , studied the function and workflow of four released algorithms of microorganism detection based on high throughput sequencing data , and analyzed their advantages and disadvantages.Finally, we summarized how these detection algorithms were designed and classified them before we proposed ways of improvement .