Evidence map›Paper›PMID 34258521›Full record

ArticleFASEB bioAdvances2021

The multiple alignments of very short sequences.

Kristóf Takács, Vince Grolmusz

Open access · goldAbstract read
In one paragraph

Article in FASEB bioAdvances, 2021. 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
0.3field-weighted citation impact, top 45% of its field
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, 4 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Kristóf TakácsPIT Bioinformatics Group Eötvös University Budapest Hungary.
Vince GrolmuszPIT Bioinformatics Group Eötvös University Budapest Hungary.ORCID https://orcid.org/0000-0001-9456-8876
Eötvös Loránd University · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The multiple sequence alignment (MSA) is an increasingly important task in bioinformatics as we have to deal with the constantly increasing gene- and protein sequence databases. MSA is applied in phylogenetic analysis, in discovering conservative protein domains, in the assignment of secondary and tertiary structural features in proteins, or in the metagenomic sample analysis and gene discovery. Usually, the focus is on the MSA of long sequences, since in the practice these tasks appear most frequently. However, the strict analysis of the optimal MSA of short sequences is an area of negligence, and findings there may contribute to better and faster algorithms for the multiple alignment of long sequences. In the present contribution, we are examining length-1 sequences using arbitrary metric and length-2 sequences using unit metric, and we show that the optimum of the MSA problem can be achieved by the trivial alignment in both cases.

Identifiers

PMID34258521
PMCPMC8255854
OpenAlexW3128396383

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.