ArticleGenome biology2011
High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing.
Article in Genome biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.
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.
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.
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Who cites it
73 citing papers in PubMed.
- Applications of Genome-wide Screening of CRISPR/Cas9 Knockout Library in Identifying Novel Molecular Targets for Xenobiotics.Environment & health (Washington, D.C.) · 2025Review
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- Functional Roles and Host Interactions ofPathogens (Basel, Switzerland) · 2025Review
- Unlocking biological mechanisms with integrative functional genomics approaches.Molecules and cells · 2024Review
- Pooled CRISPR screening of high-content cellular phenotypes using ghost cytometry.Cell reports methods · 2024Article
- Understanding cancer drug resistance withiScience · 2023Article
- The continuing evolution of barcode applications: Functional toxicology to cell lineage.Experimental biology and medicine (Maywood, N.J.) · 2022Review
- Designing libraries for pooled CRISPR functional screens of long noncoding RNAs.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Review
- Functional genomics approaches to improve pre-clinical drug screening and biomarker discovery.EMBO molecular medicine · 2021Review
- DeepVISP: Deep Learning for Virus Site Integration Prediction and Motif Discovery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Article
- Single-Cell Toolkits Opening a New Era for Cell Engineering.Molecules and cells · 2021Review
- BaSDAS: a web-based pooled CRISPR-Cas9 knockout screening data analysis system.Genomics & informatics · 2020Article
- Rapid, robust plasmid verification by de novo assembly of short sequencing reads.Nucleic acids research · 2020Article
- Article
- Advances in high-throughput methods for the identification of virus receptors.Medical microbiology and immunology · 2020Review
- Article
- Decoding pluripotency: Genetic screens to interrogate the acquisition, maintenance, and exit of pluripotency.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Highly multiplexed single-cell RNA-seq by DNA oligonucleotide tagging of cellular proteins.Nature biotechnology · 2020Article
- High-throughput chromatin screens to identify targets of senescence and aging.Translational medicine of aging · 2020Article
- Identification of novel targets for host-directed therapeutics against intracellular Staphylococcus aureus.Scientific reports · 2019Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
RNA interference (RNAi) screening is a state-of-the-art technology that enables the dissection of biological processes and disease-related phenotypes. The commercial availability of genome-wide, short hairpin RNA (shRNA) libraries has fueled interest in this area but the generation and analysis of these complex data remain a challenge. Here, we describe complete experimental protocols and novel open source computational methodologies, shALIGN and shRNAseq, that allow RNAi screens to be rapidly deconvoluted using next generation sequencing. Our computational pipeline offers efficient screen analysis and the flexibility and scalability to quickly incorporate future developments in shRNA library technology.
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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.