↓ Skip to main content

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

Overview of attention for article published in Genome Biology (Online Edition), June 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)

Mentioned by

news
9 news outlets
blogs
2 blogs
twitter
38 tweeters
patent
1 patent
googleplus
1 Google+ user

Citations

dimensions_citation
108 Dimensions

Readers on

mendeley
324 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses
Published in
Genome Biology (Online Edition), June 2016
DOI 10.1186/s13059-016-0980-6
Pubmed ID
Authors

Vanni Bucci, Belinda Tzen, Ning Li, Matt Simmons, Takeshi Tanoue, Elijah Bogart, Luxue Deng, Vladimir Yeliseyev, Mary L. Delaney, Qing Liu, Bernat Olle, Richard R. Stein, Kenya Honda, Lynn Bry, Georg K. Gerber

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.

Twitter Demographics

The data shown below were collected from the profiles of 38 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 324 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 1%
India 1 <1%
Finland 1 <1%
Japan 1 <1%
Switzerland 1 <1%
Unknown 316 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 96 30%
Researcher 71 22%
Student > Master 31 10%
Student > Doctoral Student 19 6%
Student > Bachelor 18 6%
Other 49 15%
Unknown 40 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 88 27%
Biochemistry, Genetics and Molecular Biology 52 16%
Immunology and Microbiology 34 10%
Computer Science 19 6%
Environmental Science 17 5%
Other 62 19%
Unknown 52 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 101. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 March 2020.
All research outputs
#237,286
of 17,136,794 outputs
Outputs from Genome Biology (Online Edition)
#172
of 3,562 outputs
Outputs of similar age
#6,481
of 272,446 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 2 outputs
Altmetric has tracked 17,136,794 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,562 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.4. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 272,446 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them