Integrating phenotype and gene expression data for predicting gene function

@inproceedings{Malone2009IntegratingPA,
  title={Integrating phenotype and gene expression data for predicting gene function},
  author={Brandon M. Malone and Andy D. Perkins and Susan M. Bridges},
  booktitle={BMC Bioinformatics},
  year={2009}
}
This paper presents a framework for integrating disparate data sets to predict gene function. The algorithm constructs a graph, called an integrated similarity graph, by computing similarities based upon both gene expression and textual phenotype data. This integrated graph is then used to make predictions about whether individual genes should be assigned a particular annotation from the Gene Ontology. A combined graph was generated from publicly-available gene expression data and phenotypic… CONTINUE READING

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