The Capsid Protein of Semliki Forest Virus Antagonizes RNA Interference in Mammalian Cells is a research paper published in Journal of Virology (2020). On theSindex it has a DataRank of 1.5. It has been cited 43 times, with 36 citing works in its 1-hop citation network. Its calibrated FAIR score is 61/100.
Alphaviruses are a genus of positive-stranded RNA viruses and include numerous important human pathogens, such as Chikungunya virus, Ross River virus, Western equine encephalitis virus, etc., which create the emerging and reemerging public health threat worldwide. RNA interference (RNAi) is one of the most important antiviral mechanisms in plants and insects. Accumulating evidence has provided strong support for the existence of antiviral RNAi in mammals. In response to antiviral RNAi, viruses have evolved to encode viral suppressors of RNAi (VSRs) to antagonize the RNAi pathway. It is unclear whether alphaviruses encode VSRs that can suppress antiviral RNAi during their infection in mammals. In this study, we first uncovered that capsid protein encoded by Semliki Forest virus (SFV), a prototypic alphavirus, had a potent VSR activity that can antagonize antiviral RNAi in the context of SFV infection in mammalian cells, and this mechanism is probably used by other alphaviruses.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.568
From this paper's citation signal
Citation Network Contribution
0.883
From 29 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 39% comes from its base citations and 61% from the citation network (29 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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