Probabilistic prediction of unknown metabolic and signal-transduction networks.

@article{Gomez2001ProbabilisticPO,
  title={Probabilistic prediction of unknown metabolic and signal-transduction networks.},
  author={Shawn M. Gomez and Su Hao Lo and Andrey Rzhetsky},
  journal={Genetics},
  year={2001},
  volume={159 3},
  pages={1291-8}
}
Regulatory networks provide control over complex cell behavior in all kingdoms of life. Here we describe a statistical model, based on representing proteins as collections of domains or motifs, which predicts unknown molecular interactions within these biological networks. Using known protein-protein interactions of Saccharomyces cerevisiae as training data, we were able to predict the links within this network with only 7% false-negative and 10% false-positive error rates. We also use Markov… CONTINUE READING
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