Evidence map›Paper›PMID 32075081›Full record

ArticleGenes2020

Whole-Genome

Ernesto Borrayo-Carbajal, Isaias May-Canche, Omar Paredes, J Alejandro Morales, Rebeca Romo-Vázquez, Hugo Vélez-Pérez

Abstract read
In one paragraph

Article in Genes, 2020. 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

6 authors.

Ernesto Borrayo-CarbajalElectronics Department, CUCEI, Universidad de Guadalajara, Jalisco, Mexico.ORCID 0000-0002-0752-6721
Isaias May-CancheComputer Sciences Department, CUCEI, Universidad de Guadalajara, Jalisco, Mexico.
Omar ParedesComputer Sciences Department, CUCEI, Universidad de Guadalajara, Jalisco, Mexico.ORCID 0000-0002-5382-6127
J Alejandro MoralesComputer Sciences Department, CUCEI, Universidad de Guadalajara, Jalisco, Mexico.ORCID 0000-0001-8088-9724
Rebeca Romo-VázquezComputer Sciences Department, CUCEI, Universidad de Guadalajara, Jalisco, Mexico.
Hugo Vélez-PérezComputer Sciences Department, CUCEI, Universidad de Guadalajara, Jalisco, Mexico.ORCID 0000-0003-1319-8493

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alignment-free k-mer-based algorithms in whole genome sequence comparisons remainan ongoing challenge. Here, we explore the possibility to use Topic Modeling for organismwhole-genome comparisons. We analyzed 30 complete genomes from three bacterial families bytopic modeling. For this, each genome was considered as a document and 13-mer nucleotiderepresentations as words. Latent Dirichlet allocation was used as the probabilistic modeling of thecorpus. We where able to identify the topic distribution among analyzed genomes, which is highlyconsistent with traditional hierarchical classification. It is possible that topic modeling may be appliedto establish relationships between genome's composition and biological phenomena.

Indexed as

AlgorithmsBacteriaComputational BiologyGenome, BacterialGenomicsMachine LearningModels, StatisticalPhylogenySequence AlignmentWhole Genome SequencingAlignment-FreeBacteria Genome ComparisonTopic Model

Identifiers

PMID32075081
PMCPMC7074292

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.