Evidence map›Paper›PMID 29297337›Full record

ArticleBMC systems biology2017

Reconstructing evolutionary trees in parallel for massive sequences.

Quan Zou, Shixiang Wan, Xiangxiang Zeng, Zhanshan Sam Ma

Abstract read
In one paragraph

Article in BMC systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Quan ZouSchool of Computer Science and Technology, Tianjin University, Tianjin, People's Republic of China.
Shixiang WanSchool of Computer Science and Technology, Tianjin University, Tianjin, People's Republic of China.
Xiangxiang ZengDepartment of Computer Science, Xiamen University, Xiamen, China. xzeng@xmu.edu.cn.
Zhanshan Sam MaState Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China. samma@uidaho.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBuilding the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Hadoop and Spark are developed recently, which bring spring light for the classical computational biology problems. In this paper, we tried to solve the multiple sequence alignment and evolutionary reconstruction in parallel.

resultsHPTree, which is developed in this paper, can deal with big DNA sequence files quickly. It works well on the >1GB files, and gets better performance than other evolutionary reconstruction tools. Users could use HPTree for reonstructing evolutioanry trees on the computer clusters or cloud platform (eg. Amazon Cloud). HPTree could help on population evolution research and metagenomics analysis.

conclusionsIn this paper, we employ the Hadoop and Spark platform and design an evolutionary tree reconstruction software tool for unaligned massive DNA sequences. Clustering and multiple sequence alignment are done in parallel. Neighbour-joining model was employed for the evolutionary tree building. We opened our software together with source codes via http://lab.malab.cn/soft/HPtree/ .

Indexed as

Evolution, MolecularPhylogenySoftwareAlgorithmsClassificationComputational BiologySequence AlignmentSequence Analysis, DNAAlgorithmComputational biologyEvolutionary treeHadoopMultiple sequence alignmentSpark

Identifiers

PMID29297337
PMCPMC5751538

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.