Honghui Li

An Accurate Sequence Assembly Algorithm for Livestock, Plants and Microorganism Based on Spark

Sequence Assembly is one of the important topics in bioinformatics research. Sequence assembly algorithm has always met the problems of poor assembling precision and low efficiency. In view of these two problems, this paper designs and implements a precise assembling algorithm under the strategy of finding the source of reads based on the MapReduce (SA-BR-MR) and Eulerian path algorithm. Computational results show that SA-BR-MR is more accurate than other algorithms. At the same time, SA-BR-MR calculates 54 sequences which are randomly selected from animals, plants and microorganisms with base lengths from hundreds to tens of thousands from NCBI. All matching rates of the 54 sequences are 100%. For each species, the algorithm summarizes the range of K which makes the matching rates to be 100%. In order to verify the range of K value of hepatitis C virus (HCV) and related variants, the randomly selected eight HCV variants are calculated. The results verify the correctness of K range of hepatitis C and rela...

Improved Roulette Wheel Selection-Based Genetic Algorithm for TSP

Genetic algorithms are typical swarm intelligence techniques based on the mechanics of natural selection and natural genetic, which combines artificial survival of the fittest concept with genetic operations abstracted from nature. Since the genetic algorithm has good global search capability, as well as the parallel nature of other advantages, it has been widely used in combinatorial optimization, machine learning, signal processing field, adaptive control and artificial life and so on. It is one of the key technologies related to modern intelligent calculation. Fitness proportionate selection, as a common selection method for GA, is usually implemented with method of roulette wheel selection. In this paper, an improved selection method based on fitness proportionate selection was presented. Computational results show that the method which proposed in this paper improved the result precision and better astringency by solving TSP problem.

DNA Sequence Splicing Algorithm Based on Spark

Bioinformatics is a cross subject of biological information processing. DNA sequence splicing is one of its research content. At present, most parallel algorithms are based on the operating environment of MapReduce. There is a complex process for reading and writing to hard disk, which lead to inferiority that the speed of the algorithm will be slow. In this paper, Spark calculation model based on memory is proposed to solve the problem. At the same time, a new method of matching K-2 bit will be also used by us. Results of experiment show that the running environment based on Spark and the method can ensure accuracy of stitching results and make the algorithm more efficient.