MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses

@inproceedings{Bucci2016MDSINEMD,
  title={MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses},
  author={Vanni Bucci and Belinda Tzen and Ning Li and Matt Simmons and Takeshi Tanoue and Elijah Bogart and Luxue Deng and Vladimir Yeliseyev and Mary L. Delaney and Qing Liu and Bernat Olle and Richard R. Stein and Kenya Honda and Lynn Bry and Georg K. Gerber},
  booktitle={Genome Biology},
  year={2016}
}
Predicting dynamics of host-microbial ecosystems is crucial for the rational design of bacteriotherapies. We present MDSINE, a suite of algorithms for inferring dynamical systems models from microbiome time-series data and predicting temporal behaviors. Using simulated data, we demonstrate that MDSINE significantly outperforms the existing inference method. We then show MDSINE’s utility on two new gnotobiotic mice datasets, investigating infection with Clostridium difficile and an immune… CONTINUE READING
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