ArticleInternational journal for parasitology2018
Refined ab initio gene predictions of Heterorhabditis bacteriophora using RNA-seq.
Article in International journal for parasitology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Chemogenomic approach to identifying nematode chemoreceptor drug targets in the entomopathogenic nematode Heterorhabditis bacteriophora.Computational biology and chemistry · 2021Article
- GFF Utilities: GffRead and GffCompare.F1000Research · 2020Article
- Molecular Regulators of Entomopathogenic Nematode-Bacterial Symbiosis.Results and problems in cell differentiation · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Interest has recently grown in developing the entomopathogenic nematode Heterorhabditis bacteriophora as a model to genetically dissect the process of parasitic infection. Despite the availability of a full genome assembly, there is substantial variation in gene model accuracy. Here, a methodology is presented for leveraging RNA-seq evidence to generate improved annotations using ab initio gene prediction software. After alignment of reads and subsequent generation of a RNA-seq supported annotation, the new gene prediction models were verified on a selection of genes by comparison with sequenced 5' and 3' rapid amplification of cDNA ends products. By utilising a whole transcriptome for genome annotation, the current reference annotation was enriched, demonstrating the importance of coupling transcriptional data with genome assemblies.
Indexed as
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.