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HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing

Overview of attention for article published in Algorithms for Molecular Biology, September 2017
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Title
HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing
Published in
Algorithms for Molecular Biology, September 2017
DOI 10.1186/s13015-017-0116-x
Pubmed ID
Authors

Shixiang Wan, Quan Zou

Abstract

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 25%
Researcher 5 11%
Student > Master 5 11%
Professor > Associate Professor 3 7%
Other 3 7%
Other 3 7%
Unknown 14 32%
Readers by discipline Count As %
Computer Science 11 25%
Biochemistry, Genetics and Molecular Biology 6 14%
Agricultural and Biological Sciences 6 14%
Engineering 3 7%
Mathematics 1 2%
Other 2 5%
Unknown 15 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 October 2017.
All research outputs
#18,572,844
of 23,003,906 outputs
Outputs from Algorithms for Molecular Biology
#197
of 264 outputs
Outputs of similar age
#246,007
of 321,103 outputs
Outputs of similar age from Algorithms for Molecular Biology
#2
of 6 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 321,103 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.