.png){kind=icon}
返回
Parallel implementation of D-Phylo algorithm for maximum likelihood clusters
.png){kind=icon}
OA
AI
DOI：10.1049/iet-nbt.2016.0005.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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 x 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.
Keyword:
PHYLOGENETIC ANALYSIS
EVOLUTIONARY TREES
SYSTEMATIC BIASES
SELECTION
MODELS
CONSTRUCTION
CHARACTERS
TOOL
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.9
论文数:
1.1K
被引数:
3.0K
机构
引用论文
PartitionFinder: Combined Selection of Partitioning Schemes and Substitution Models for Phylogenetic AnalysesPartitionFinder: 用于系统发育分析的分区方案和替代模型的组合选择
OAAI
OAAI分享收藏A Method for Inferring the Rate of Evolution of Homologous Characters that Can Potentially Improve Phylogenetic Inference, Resolve Deep Divergence and Correct Systematic Biases.png)
SYSTEMATIC BIOLOGYOAAI
SYSTEMATIC BIOLOGYIF5.7
OAAI分享收藏分享收藏
查看更多内容