ReviewFrontiers in genome editing2023
Genome-wide CRISPR screens and their applications in infectious disease.
Review in Frontiers in genome editing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 8 citations in OpenAlex.
- High-Content CRISPR Screening: Methods and Applications.MedComm · 2026Review
- A graph-based learning approach to predict the effects of gene perturbations on molecular phenotypes.bioRxiv : the preprint server for biology · 2026Article
- Host Cell Virus Interactions: Molecular Mechanisms, Immune Modulation, Viral Pathogenesis, and Emerging Therapeutic Targets.Viruses · 2026Review
- Host cyclophilin-mediated maturation of an obligate intracellular bacterial surface virulence factor.bioRxiv : the preprint server for biology · 2025Article
- Application of CRISPR/Cas gene editing for infectious disease control in poultry.Open life sciences · 2025Review
- Building a human lung from pluripotent stem cells to model respiratory viral infections.Respiratory research · 2024Review
- CRISPR/Cas9-based mutant library screening: the discovery of novel genes regulating immune responses in cotton and rice.Frontiers in plant science · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inactivation or targeted disruption of a gene provides clues to assess the function of the gene in many cellular processes. Knockdown or knocking out a gene has been widely used for this purpose. However, recently CRISPR mediated genome editing has taken over the knockout/knockdown system with more precision. CRISPR technique has enabled us to perform targeted mutagenesis or genome editing to address questions in fundamental biology to biomedical research. Its application is wide in understanding the role of genes in the disease process, and response to therapy in cancer, metabolic disorders, or infectious disease. In this article, we have focused on infectious disease and how genome-wide CRISPR screens have enabled us to identify host factors involved in the process of infection. Understanding the biology of the host-pathogen interaction is of immense importance in planning host-directed therapy to improve better management of the disease. Genome-wide CRISPR screens provide strong mechanistic ways to identify the host dependency factors involved in various infections. We presented insights into genome-wide CRISPR screens conducted in the context of infectious diseases both viral and bacterial that led to better understanding of host-pathogen interactions and immune networks. We have discussed the advancement of knowledge pertaining to influenza virus, different hepatitis viruses, HIV, most recent SARS CoV2 and few more. Among bacterial diseases, we have focused on infection with life threatening
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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.