ArticleGenome research2008
Finding friends and enemies in an enemies-only network: a graph diffusion kernel for predicting novel genetic interactions and co-complex membership from yeast genetic interactions.
Article in Genome research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- ONCOPLEX: an oncology-inspired hypergraph model integrating diverse biological knowledge for cancer driver gene prediction.Scientific reports · 2026Article
- Prioritizing drug targets by perturbing biological network response functions.PLoS computational biology · 2024Article
- MPASL: multi-perspective learning knowledge graph attention network for synthetic lethality prediction in human cancer.Frontiers in pharmacology · 2024Article
- Linking cells across single-cell modalities by synergistic matching of neighborhood structure.Bioinformatics (Oxford, England) · 2022Article
- Computational identification of biomarker genes for lung cancer considering treatment and non-treatment studies.BMC bioinformatics · 2020Article
- uKIN Combines New and Prior Information with Guided Network Propagation to Accurately Identify Disease Genes.Cell systems · 2020Article
- Using deep maxout neural networks to improve the accuracy of function prediction from protein interaction networks.PloS one · 2019Article
- Article
- Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.BMC systems biology · 2017Article
- Network propagation: a universal amplifier of genetic associations.Nature reviews. Genetics · 2017Review
- Linearity of network proximity measures: implications for set-based queries and significance testing.Bioinformatics (Oxford, England) · 2017Article
- Predictability of Genetic Interactions from Functional Gene Modules.G3 (Bethesda, Md.) · 2017Article
- A Concise Review on Multi-Omics Data Integration for Terroir Analysis inFrontiers in plant science · 2017Review
- Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules.Scientific reports · 2016Article
- Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems.Cell systems · 2016Article
- Methods for the integration of multi-omics data: mathematical aspects.BMC bioinformatics · 2016Article
- Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer.Biology direct · 2015Article
- Data Imputation in Epistatic MAPs by Network-Guided Matrix Completion.Journal of computational biology : a journal of computational molecular cell biology · 2015Article
- Prediction of Genetic Interactions Using Machine Learning and Network Properties.Frontiers in bioengineering and biotechnology · 2015Review
- Article
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Authors and funding
5 authors.
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Abstract
The yeast synthetic lethal genetic interaction network contains rich information about underlying pathways and protein complexes as well as new genetic interactions yet to be discovered. We have developed a graph diffusion kernel as a unified framework for inferring complex/pathway membership analogous to "friends" and genetic interactions analogous to "enemies" from the genetic interaction network. When applied to the Saccharomyces cerevisiae synthetic lethal genetic interaction network, we can achieve a precision around 50% with 20% to 50% recall in the genome-wide prediction of new genetic interactions, supported by experimental validation. The kernels show significant improvement over previous best methods for predicting genetic interactions and protein co-complex membership from genetic interaction data.
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