ArticleNature genetics2011
An integrated approach to characterize genetic interaction networks in yeast metabolism.
Article in Nature genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 119 papers.
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Who cites it
119 citing papers in PubMed, 219 citations in OpenAlex.
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- Minimisation of metabolic networks defines a new functional class of genes.Nature communications · 2024Article
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- The origins of the Guinness stout yeast.Communications biology · 2024Article
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- Leveraging the genetic correlation between traits improves the detection of epistasis in genome-wide association studies.G3 (Bethesda, Md.) · 2023Article
- From genotype to phenotype: computational approaches for inferring microbial traits relevant to the food industry.FEMS microbiology reviews · 2023Review
- Integration of probabilistic functional networks without an external Gold Standard.BMC bioinformatics · 2022Article
- Understudied proteins: opportunities and challenges for functional proteomics.Nature methods · 2022Article
- Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges.Biomolecules · 2022Review
- Give and take in the exometabolome.Nature microbiology · 2022Article
- From Petri Plates to Petri Nets, a revolution in yeast biology.FEMS yeast research · 2022Article
- Exploring synergies between plant metabolic modelling and machine learning.Computational and structural biotechnology journal · 2022Review
- Path to improving the life cycle and quality of genome-scale models of metabolism.Cell systems · 2021Review
- Suboptimal Global Transcriptional Response Increases the Harmful Effects of Loss-of-Function Mutations.Molecular biology and evolution · 2021Article
- Article
- Employing Cross-Species Approaches to Construct Humanized Genetic Interaction Networks.Methods in molecular biology (Clifton, N.J.) · 2021Article
59 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
15 authors at 9 institutions in 5 countries.
Funding
Abstract
Although experimental and theoretical efforts have been applied to globally map genetic interactions, we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we i, quantitatively measured genetic interactions between ∼185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii, superposed the data on a detailed systems biology model of metabolism and iii, introduced a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigated the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy and gene dispensability. Last, we show the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments.
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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.