@article{044dcdff61df4a1e8a49b2562af47eb7,
title = "MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses",
abstract = "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-modulatory probiotic. Using these datasets, we demonstrate new capabilities, including accurate forecasting of microbial dynamics, prediction of stable sub-communities that inhibit pathogen growth, and identification of bacteria most crucial to community integrity in response to perturbations.",
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 Delaney, {Mary L.} and Qing Liu and Bernat Olle and Stein, {Richard R.} and Kenya Honda and Lynn Bry and Gerber, {Georg K.}",
note = "Funding Information: This work was supported by the Defense Advanced Projects Agency Biological Robustness in Complex Settings program (DARPA BRICS award HR0011-15-C-0094) and grants from the Harvard Digestive Diseases Center (Pilot and Feasibility Grant to GKG and Core Grant to LB, under NIH Grant P30DK034854), the National Heart, Lung and Blood Institute (grant 2T32HL007627-31 supporting EB), the National Institute of Allergy and Infectious Disease (grant R15-AI112985-01A1 supporting VB), and the National Science Foundation (grant 1458347 supporting VB). GKG also acknowledges support from the Brigham and Women{\textquoteright}s Hospital Department of Pathology. Publisher Copyright: {\textcopyright} 2016 Bucci et al.",
year = "2016",
month = jun,
day = "3",
doi = "10.1186/s13059-016-0980-6",
language = "English",
volume = "17",
journal = "Genome Biology",
issn = "1474-7596",
publisher = "BioMed Central",
number = "1",
}