Evidence map›Paper›PMID 31409290›Full record

ArticleBMC bioinformatics2019

LS

Carlos J Rivera-Rivera, Juan I Montoya-Burgos

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 2019. 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. Review
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.

Carlos J Rivera-RiveraDepartment of Genetics and Evolution, University of Geneva, Quai Ernest-Ansermet 30, 1211, Geneva, Switzerland.
Juan I Montoya-BurgosDepartment of Genetics and Evolution, University of Geneva, Quai Ernest-Ansermet 30, 1211, Geneva, Switzerland. juan.montoya@unige.ch.

Funding

Institute of Genetics and Genomics in Geneva (iGE3) N/ASchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH) 31003A_141233
6 · The paper itself

Abstract

backgroundLineage rate heterogeneity can be a major source of bias, especially in multi-gene phylogeny inference. We had previously tackled this issue by developing LS

resultsWe address these challenges and produce a new, platform-independent program, LS

conclusionsLS

Indexed as

Biological EvolutionEvolution, MolecularSoftwareAlgorithmsComputational BiologyPhylogenyLineage rate heterogeneityLong branch attractionPhylogenetic methodsPhylogenomicsSequence subsampling

Identifiers

PMID31409290
PMCPMC6693147

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.