Proteome Analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations

@article{Szafron2004ProteomeAC,
  title={Proteome Analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations},
  author={Duane Szafron and Paul Lu and Russell Greiner and David S. Wishart and Brett Poulin and Roman Eisner and Zhiyong Lu and John Anvik and Cam Macdonell and Alona Fyshe and David Meeuwis},
  journal={Nucleic acids research},
  year={2004},
  volume={32 Web Server issue},
  pages={
          W365-71
        }
}
Proteome Analyst (PA) (http://www.cs.ualberta.ca/~bioinfo/PA/) is a publicly available, high-throughput, web-based system for predicting various properties of each protein in an entire proteome. Using machine-learned classifiers, PA can predict, for example, the GeneQuiz general function and Gene Ontology (GO) molecular function of a protein. In addition, PA is currently the most accurate and most comprehensive system for predicting subcellular localization, the location within a cell where a… CONTINUE READING

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Key Quantitative Results

  • After only two rounds, we were able to create a final custom classifier that is 100% accurate, over 5-fold cross-validation, with respect to the training data.
  • We constructed five custom classifiers for predicting subcellular localization of proteins from animals, plants, fungi, Gram-negative bacteria and Gram-positive bacteria which are 81% accurate for fungi and 92–94% accurate for the other four categories (Table 1).

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