Parallel implementation of D-Phylo algorithm for maximum likelihood clusters

IET Nanobiotechnol. 2017 Mar;11(2):134-142. doi: 10.1049/iet-nbt.2016.0005.

Abstract

This study explains a newly developed parallel algorithm for phylogenetic analysis of DNA sequences. The newly designed D-Phylo is a more advanced algorithm for phylogenetic analysis using maximum likelihood approach. The D-Phylo while misusing the seeking capacity of k-means keeps away from its real constraint of getting stuck at privately conserved motifs. The authors have tested the behaviour of D-Phylo on Amazon Linux Amazon Machine Image(Hardware Virtual Machine)i2.4xlarge, six central processing unit, 122 GiB memory, 8 × 800 Solid-state drive Elastic Block Store volume, high network performance up to 15 processors for several real-life datasets. Distributing the clusters evenly on all the processors provides us the capacity to accomplish a near direct speed if there should arise an occurrence of huge number of processors.

MeSH terms

  • Algorithms*
  • Conserved Sequence / genetics
  • DNA, Viral / genetics*
  • Data Interpretation, Statistical
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Likelihood Functions
  • Multigene Family / genetics
  • Pattern Recognition, Automated / methods
  • Phylogeny*
  • Sequence Alignment / methods*
  • Sequence Analysis, DNA / methods*
  • Software

Substances

  • DNA, Viral