Evidence map›Paper›PMID 36703866›Full record

ArticleEvolutionary bioinformatics online2023

G-SAIP: Graphical Sequence Alignment Through Parallel Programming in the Post-Genomic Era.

Johan S Piña, Simon Orozco-Arias, Nicolas Tobón-Orozco, Leonardo Camargo-Forero, Reinel Tabares-Soto, Romain Guyot

Abstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2023. 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

6 authors.

Johan S PiñaDepartment of Data Science, People Contact, Manizales, Caldas, Colombia.ORCID https://orcid.org/0000-0003-4760-7232
Simon Orozco-AriasDepartment of Computer Science, Universidad Autónoma de Manizales, Manizales, Caldas, Colombia.
Nicolas Tobón-OrozcoDepartment of Computer Science, Universidad Autónoma de Manizales, Manizales, Caldas, Colombia.
Leonardo Camargo-ForeroUbiHPC, Bucaramanga, Colombia.
Reinel Tabares-SotoDepartment of Electronics and Automation, Universidad Autónoma de Manizales, Manizales, Caldas, Colombia.
Romain GuyotDepartment of Electronics and Automation, Universidad Autónoma de Manizales, Manizales, Caldas, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A common task in bioinformatics is to compare DNA sequences to identify similarities between organisms at the sequence level. An approach to such comparison is the dot-plots, a 2-dimensional graphical representation to analyze DNA or protein alignments. Dot-plots alignment software existed before the sequencing revolution, and now there is an ongoing limitation when dealing with large-size sequences, resulting in very long execution times. High-Performance Computing (HPC) techniques have been successfully used in many applications to reduce computing times, but so far, very few applications for graphical sequence alignment using HPC have been reported. Here, we present G-SAIP (Graphical Sequence Alignment in Parallel), a software capable of spawning multiple distributed processes on CPUs, over a supercomputing infrastructure to speed up the execution time for dot-plot generation up to 1.68× compared with other current fastest tools, improve the efficiency for comparative structural genomic analysis, phylogenetics because the benefits of pairwise alignments for comparison between genomes, repetitive structure identification, and assembly quality checking.

Indexed as

bioinformaticsdot-plotsgraphical alignmentsG-SAIPHPCpost-genomic era

Identifiers

PMID36703866
PMCPMC9871978

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.