ArticleMobile genetic elements2011
In search of lost trajectories: Recovering the diversification of transposable elements.
Article in Mobile genetic elements, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Computational Evaluation of the Strict Master and Random Template Models of Endogenous Retrovirus Evolution.PloS one · 2016Article
- Accommodating the load: The transposable element content of very large genomes.Mobile genetic elements · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transposable elements (TEs) are DNA sequences that have the capacity to move and duplicate within genomes, and occasionally between them. They are present in almost all species and are especially prevalent in eukaryotes where they can account for most of the genomic content. As a result of their dynamics and their mere presence, TEs can profoundly shape genomes and gene expression. With the current pace of sequencing technology improvement, a rapidly increasing number of genomes, particularly from non-model species, are being sequenced. However, the complete annotation of these genomes and especially of the TEs they contain, still poses fundamental difficulties. In a recent article, we presented a combined method that automatically annotates TEs with accuracy and sensitivity, and takes their diversification dynamics into account in the de novo annotation process. Here, we further discuss several additional aspects of our results, notably in the light of our knowledge of TE dynamics and the conceptual model behind the TE detection algorithms currently in use. In addition, we propose a new approach that uses simulations to improve algorithm performance.
Identifiers
What OpenQuestion holds
Registered trials
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.