Design And Implementation Of Omics Data Analysis Optimization Based On Distributed Systems

Omics data is used to describe various types of biological objects,which comes from the systematic study of biology.With the development of high-throughput sequencing technology,the distributed technology has been adopted by the omics data analysis increasingly to answer the challenge.In order to relieve the lagging situation in china,this paper builds a distributed computing analysis platform for omics data analysis,and optimizes the retrieval and computing problems in omics data analysis.Firstly,this paper designs a retrieval optimization model to solve the omics data retrieval problems.Based on the key-value pair databases,it realizes a multi?dimensional ordered organization for omics data sets.Meanwhile,to enhance applicability of different applications,this model uses user defined functions to evaluate data content in the reading and writing process.Secondly,this paper analyzes and discusses the parallelization algorithm design in the omics data analysis to break performance of the traditional analysis methods.By comparing the different parallelization implementations of BLAST,it proposes the rationality of equilibrium principle in parallelization optimization design.Thirdly,this paper analyzes the comparison results which are produced by different parallelization BLAST.It is proved that the equilibrium principle is effective for omics data analysis optimization.Finally,this paper designs and implements related systems and applications based on the proposed optimization method.