ArticleBioinformatics (Oxford, England)2008
Physical protein-protein interactions predicted from microarrays.
Article in Bioinformatics (Oxford, England), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- A simple and rapid pipeline for identification of receptor-binding sites on the surface proteins of pathogens.Scientific reports · 2020Article
- A Computational Framework for Predicting Direct Contacts and Substructures within Protein Complexes.Biomolecules · 2019Article
- Protein Complex Identification and quantitative complexome by CN-PAGE.Scientific reports · 2019Article
- Computational identification of protein-protein interactions in model plant proteomes.Scientific reports · 2019Article
- A computational framework for distinguishing direct versus indirect interactions in human functional protein-protein interaction networks.Integrative biology : quantitative biosciences from nano to macro · 2017Article
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- Fusion of clinical and stochastic finite element data for hip fracture risk prediction.Journal of biomechanics · 2015Article
- Article
- A network-based approach for predicting missing pathway interactions.PLoS computational biology · 2012Article
- Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks.BMC genomics · 2011Article
- Partner-aware prediction of interacting residues in protein-protein complexes from sequence data.PloS one · 2011Article
- Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines.BMC bioinformatics · 2010Article
- Revealing and avoiding bias in semantic similarity scores for protein pairs.BMC bioinformatics · 2010Article
- Predicting protein-protein interactions in unbalanced data using the primary structure of proteins.BMC bioinformatics · 2010Article
- Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences.BMC bioinformatics · 2009Article
- Integrating diverse information to gain more insight into microarray analysis.Journal of biomedicine & biotechnology · 2009Article
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Authors and funding
3 authors.
Funding
Abstract
motivationMicroarray expression data reveal functionally associated proteins. However, most proteins that are associated are not actually in direct physical contact. Predicting physical interactions directly from microarrays is both a challenging and important task that we addressed by developing a novel machine learning method optimized for this task.
resultsWe validated our support vector machine-based method on several independent datasets. At the same levels of accuracy, our method recovered more experimentally observed physical interactions than a conventional correlation-based approach. Pairs predicted by our method to very likely interact were close in the overall network of interaction, suggesting our method as an aid for functional annotation. We applied the method to predict interactions in yeast (Saccharomyces cerevisiae). A Gene Ontology function annotation analysis and literature search revealed several probable and novel predictions worthy of future experimental validation. We therefore hope our new method will improve the annotation of interactions as one component of multi-source integrated systems. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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