Parallel implementation of D‐Phylo algorithm for maximum likelihood clusters. Issue 2 (29th July 2016)

• Record Type: Journal Article
• Authors: Malik, Shamita; Sharma, Dolly; Khatri, Sunil Kumar
• Is Part Of: IET nanobiotechnology. Volume 11:Issue 2(2017)
• Page Start: 134
• Page End: 142
• Publication Date: 2016-07-29
• Subjects: parallel algorithms -- Linux -- pattern clustering -- DNA -- molecular biophysics -- genetics -- biology computing; D‐Phylo algorithm parallel implementation -- maximum likelihood clusters -- DNA sequence phylogenetic analysis -- Amazon Linux AMI -- HVM -- central processing unit -- SSD -- real‐life datasets -- processors -- high‐network performance; Biotechnology -- Periodicals; Nanotechnology -- Periodicals; 660.6
• DOI: 10.1049/iet-nbt.2016.0005
• Languages: English
• ISSNs: 1751-8741

Abstract

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.