ArticleScientific reports2017
An optimistic protein assembly from sequence reads salvaged an uncharacterized segment of mouse picobirnavirus.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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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.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Discovery and genetic characterization of diverse smacoviruses in Zambian non-human primates.Scientific reports · 2019Article
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in Next Generation Sequencing technologies have enabled the generation of millions of sequences from microorganisms. However, distinguishing the sequence of a novel species from sequencing errors remains a technical challenge when the novel species is highly divergent from the closest known species. To solve such a problem, we developed a new method called Optimistic Protein Assembly from Reads (OPAR). This method is based on the assumption that protein sequences could be more conserved than the nucleotide sequences encoding them. By taking advantage of metagenomics, bioinformatics and conventional Sanger sequencing, our method successfully identified all coding regions of the mouse picobirnavirus for the first time. The salvaged sequences indicated that segment 1 of this virus was more divergent from its homologues in other Picobirnaviridae species than segment 2. For this reason, only segment 2 of mouse picobirnavirus has been detected in previous studies. OPAR web tool is available at http://bioinformatics.czc.hokudai.ac.jp/opar/.
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