Evidence map›Paper›PMID 32993484›Full record

ArticleBMC bioinformatics2020

pmTM-align: scalable pairwise and multiple structure alignment with Apache Spark and OpenMP.

Weiya Chen, Chun Yao, Yingzhong Guo, Yan Wang, Zhidong Xue

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Weiya ChenSchool of Software Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China.
Chun YaoSchool of Software Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China.
Yingzhong GuoSchool of Software Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China.
Yan WangSchool of Life Science, Huazhong University of Science and Technology, Wuhan, China.
Zhidong XueSchool of Software Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China. zdxue@hust.edu.cn.ORCID http://orcid.org/0000-0003-3559-0867

Funding

National Natural Science Foundation of China 61772217
6 · The paper itself

Abstract

backgroundStructure comparison can provide useful information to identify functional and evolutionary relationship between proteins. With the dramatic increase of protein structure data in the Protein Data Bank, computation time quickly becomes the bottleneck for large scale structure comparisons. To more efficiently deal with informative multiple structure alignment tasks, we propose pmTM-align, a parallel protein structure alignment approach based on mTM-align/TM-align. pmTM-align contains two stages to handle pairwise structure alignments with Spark and the phylogenetic tree-based multiple structure alignment task on a single computer with OpenMP.

resultsExperiments with the SABmark dataset showed that parallelization along with data structure optimization provided considerable speedup for mTM-align. The Spark-based structure alignments achieved near ideal scalability with large datasets, and the OpenMP-based construction of the phylogenetic tree accelerated the incremental alignment of multiple structures and metrics computation by a factor of about 2-5.

conclusionspmTM-align enables scalable pairwise and multiple structure alignment computing and offers more timely responses for medium to large-sized input data than existing alignment tools such as mTM-align.

Indexed as

SoftwareAlgorithmsDatabases, ProteinProteinsSequence AlignmentProteinsApache SparkMultiple structure alignmentOpenMPPairwise structure alignment

Identifiers

PMID32993484
PMCPMC7526426

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.