Genome-wide analysis of host-encoded microRNAs modulating SARS-CoV-2 infection
Bibliographic record
Abstract
Viruses exploit cellular machinery to complete their replication cycle. Furthering our understanding of this process provides insight into the mechanism of virus replication and potential targets for antiviral therapeutics. Genome-wide CRISPR screens have identified cellular pathways important in the SARS-COV-2 infection process, including vesicular traffic, lipid homeostasis and PI3K signalling. Functional genomics-driven analysis of host-encoded microRNAs (miRNAs) impacting SARS-CoV-2 infection would provide further unbiased and discovery-driven insight into the host-pathogen interface. Here we present findings from genome-wide complementary miRNA mimic and inhibitor screens performed in a bio-safety level (BSL)-4 laboratory using a combination of high-throughput robotics, high-content imaging and novel data analysis pipelines. This dataset has identified both miRNA promoters and inhibitors of SARS-CoV-2 replication which may be used by researchers to further explore therapeutic targets against SARS-CoV-2 and the host factors influencing COVID pathogenesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".