ArticleNature protocols2014
Measuring genetic interactions in human cells by RNAi and imaging.
Article in Nature protocols, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Metformin inhibits pancreatic cancer metastasis caused by SMAD4 deficiency and consequent HNF4G upregulation.Protein & cell · 2021Article
- Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning.Proceedings of machine learning research · 2019Article
- Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae.BMC biology · 2016Article
- The Deubiquitinase USP47 Stabilizes MAPK by Counteracting the Function of the N-end Rule ligase POE/UBR4 in Drosophila.PLoS biology · 2016Article
- A protocol for the systematic and quantitative measurement of protein-lipid interactions using the liposome-microarray-based assay.Nature protocols · 2016Article
- A high-content platform to characterise human induced pluripotent stem cell lines.Methods (San Diego, Calif.) · 2016Article
- The systematic analysis of protein-lipid interactions comes of age.Nature reviews. Molecular cell biology · 2015Review
- Prediction of Genetic Interactions Using Machine Learning and Network Properties.Frontiers in bioengineering and biotechnology · 2015Review
- Systems medicine: evolution of systems biology from bench to bedside.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Observation of how genetic interactions modulate phenotypes is a powerful method for dissecting their underlying molecular and functional networks. Whereas in model organisms genetic interaction studies are well established, systematic analysis of genetic interactions in human cells has remained challenging. Here we provide a detailed protocol for large-scale mapping of genetic interactions in human cells using a high-throughput phenotyping approach. Pairwise gene product depletion is induced by siRNA-mediated knockdown, and the resulting phenotypes are quantified by automated imaging and computational analysis to provide the basis for detecting genetic interactions between all pairs of genes tested. The whole workflow, depending on the size of the experiment, takes 3 or more weeks to complete.
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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.