Evidence map›Paper›PMID 39264950›Full record

ArticlePloS one2024

Gene sequence analysis model construction based on k-mer statistics.

Dongjie Gao

Abstract read
In one paragraph

Article in PloS one, 2024. 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

1 author.

Dongjie GaoSchool of Mathematics and Statistics, Heze University, Heze, China.ORCID 0000-0001-5198-8133

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of biotechnology, gene sequencing methods are gradually improved. The structure of gene sequences is also more complex. However, the traditional sequence alignment method is difficult to deal with the complex gene sequence alignment work. In order to improve the efficiency of gene sequence analysis, D2 series method of k-mer statistics is selected to build the model of gene sequence alignment analysis. According to the structure of the foreground sequence, the sequence to be aligned can be cut by different lengths and divided into multiple subsequences. Finally, according to the selected subsequences, the maximum dissimilarity in the alignment results is determined as the statistical result. At the same time, the research also designed an application system for the sequence alignment analysis of the model. The experimental results showed that the statistical power of the sequence alignment analysis model was directly proportional to the sequence coverage and cutting length, and inversely proportional to the K value and module length. At the same time, the model was applied to the system designed in this paper. The maximum storage capacity of the system was 71 GB, the maximum disk capacity was 135 GB, and the running time was less than 2.0s. Therefore, the k-mer statistic sequence alignment model and system proposed in this study have considerable application value in gene alignment analysis.

Indexed as

Sequence AlignmentAlgorithmsComputational BiologyModels, GeneticModels, StatisticalSequence Analysis, DNA

Identifiers

PMID39264950
PMCPMC11392344

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.