ArticleCommunicative & integrative biology2009
The functional relationships underlying a synthetic genetic network.
Article in Communicative & integrative biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Computational Approaches to Identify Genetic Interactions for Cancer Therapeutics.Journal of integrative bioinformatics · 2017Article
- Targeting C4-demethylating genes in the cholesterol pathway sensitizes cancer cells to EGF receptor inhibitors via increased EGF receptor degradation.Cancer discovery · 2013Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Here, we focus on synthetic lethal genetic interactions, examples of genetic enhancements, where mutations in two different genes result in lethality but only when present together. We recently identified the synthetic lethal network around the PKC1 gene encoding the essential protein kinase C of yeast. We found that this network is heavily enriched for interactions with genes whose products are closely linked to Pkc1 signaling in vivo. Here, we show that: the PKC1 gene elicits a distinct spectrum of genetic interactions to SLT2, encoding a non-essential component of the very same signaling pathway. We also show that the terminal phenotype underlying the synthetic lethal network around PKC1 is not uniform. Synthetic lethal genetic networks thus appear to be very heterogeneous in nature with important implications for what functional relationships can be discovered from them.
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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.