Evidence map›Paper›PMID 36360242›Full record

ArticleGenes2022

Heuristic Pairwise Alignment in Database Environments.

Panna Lipták, Attila Kiss, János Márk Szalai-Gindl

Abstract read
In one paragraph

Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Panna LiptákDepartment of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, Hungary.ORCID 0000-0003-4229-4599
Attila KissDepartment of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, Hungary.ORCID 0000-0001-8174-6194
János Márk Szalai-GindlDepartment of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, Hungary.ORCID 0000-0002-0169-0547

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological data have gained wider recognition during the last few years, although managing and processing these data in an efficient way remains a challenge in many areas. Increasingly, more DNA sequence databases can be accessed; however, most algorithms on these sequences are performed outside of the database with different bioinformatics software. In this article, we propose a novel approach for the comparative analysis of sequences, thereby defining heuristic pairwise alignment inside the database environment. This method takes advantage of the benefits provided by the database management system and presents a way to exploit similarities in data sets to quicken the alignment algorithm. We work with the column-oriented MonetDB, and we further discuss the key benefits of this database system in relation to our proposed heuristic approach.

Indexed as

HeuristicsSoftwareAlgorithmsComputational BiologySequence Alignmentbioinformaticsdatabase systemspairwise alignment

Identifiers

PMID36360242
PMCPMC9690874

What OpenQuestion holds

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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.