Article

Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data

2021-11-27

Abstract excerpt

The microbial interactions within the human microbiome are complex and temporally dynamic, but few methods are available to model this system within a longitudinal network framework. Based on general longitudinal 16S rRNA sequence data, we propose a stationary Gaussian graphical model (SGGM) for microbial interaction networks (MIN) which can accommodate the possible correlations between the high-dimensional observ...

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Literature Corpus work: 0b5ba134-e189-535f-b44f-79f11b8f3c78
DOI: 10.1101/2021.11.26.470159

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