Evidence map›Paper›PMID 23926417›Full record

ArticleEvolutionary bioinformatics online2013

Identification of differentially evolved genes: an alternative approach to detection of accelerated molecular evolution from genome-wide comparative data.

Kyu-Won Kim, David W Burt, Heebal Kim, Seoae Cho

Abstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2013. 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

4 authors.

Kyu-Won KimInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Korea.
David W Burt
Heebal Kim
Seoae Cho

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the most important measures for detecting molecular adaptations between species/lineages at the gene level is the comparison of relative fixation rates of synonymous (dS) and non-synonymous (dN) mutations. This study shows that the branch model is sensitive to tree topology and proposes an alternative approach, devogs, which does not require phylogenetic topology for analysis. We compared devogs with a branch model method using virtual data and a varying ω ratio, in which parameters were obtained from real data. The positive predictive value, sensitivity, and specificity of the branch model were affected by the phylogenic tree topology. Devogs showed greater positive predictive value, whereas the branch model method had greater sensitivity. In a working example using devogs, a group of human RNA polymerase II-related genes, which are important in mediating alternative splicing, were significantly accelerated compared to four other mammals.

Indexed as

branch modeldevogsdN/dS

Identifiers

PMID23926417
PMCPMC3733729

What OpenQuestion holds

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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.