ArticleGenome biology2008
Modeling synthetic lethality.
Article in Genome biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Review
- Identifying collateral and synthetic lethal vulnerabilities within the DNA-damage response.BMC bioinformatics · 2021Article
- Quantitative Genetic Screens for Mapping Bacterial Pathways and Functional Networks.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Synthetic Lethality through the Lens of Medicinal Chemistry.Journal of medicinal chemistry · 2020Review
- Membrane proteomic analysis reveals overlapping and independent functions of Streptococcus mutans Ffh, YidC1, and YidC2.Molecular oral microbiology · 2019Article
- Cooperative genomic alteration network reveals molecular classification across 12 major cancer types.Nucleic acids research · 2017Article
- A synthetic lethal approach for compound and target identification in Staphylococcus aureus.Nature chemical biology · 2016Article
- Connectivity Homology Enables Inter-Species Network Models of Synthetic Lethality.PLoS computational biology · 2015Article
- Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer.Biology direct · 2015Article
- Development of synthetic lethality anticancer therapeutics.Journal of medicinal chemistry · 2014Review
- Parallel universes of Black Six biology.Biology direct · 2014Article
- Article
- Syn-lethality: an integrative knowledge base of synthetic lethality towards discovery of selective anticancer therapies.BioMed research international · 2014Article
- Article
- Mapping bacterial functional networks and pathways in Escherichia Coli using synthetic genetic arrays.Journal of visualized experiments : JoVE · 2012Article
- Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters.Proteome science · 2012Article
- Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations.PLoS computational biology · 2012Article
- Genetic interaction maps in Escherichia coli reveal functional crosstalk among cell envelope biogenesis pathways.PLoS genetics · 2011Article
- Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions.BMC systems biology · 2011Article
- Quantitative maps of genetic interactions in yeast - comparative evaluation and integrative analysis.BMC systems biology · 2011Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSynthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units.
resultsIn Saccharomyces cerevisiae, we identified multi-protein complexes and pairs of multi-protein complexes that share an unusually high number of synthetic genetic interactions. As previously predicted, we found that synthetic lethality can arise from subunits of an essential multi-protein complex or between pairs of multi-protein complexes. Finally, using multi-protein complexes allowed us to take into account the pleiotropic nature of the gene products.
conclusionsModeling synthetic lethality using current estimates of the yeast interactome is an efficient approach to disentangle some of the complex molecular interactions that drive a cell. Our model in conjunction with applied statistical methods and computational methods provides new tools to better characterize synthetic genetic interactions.
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