Digital twin of infant microbiome (qnet models)

<p>The complexity of the gut ecosystem, with thousands of&nbsp;cross-talking microbial colonizers, together with sparsely observed abundance profiles, has limited progress. We have developed a computational framework to learn an approximate &ldquo;digital twin&rdquo; of the maturing infant microbiome,&nbsp;that once learned, can reliably forecast detailed ecosystem trajectories unfolding over weeks from few initial&nbsp;observations. This generative model (Q-net), inferred at the level of taxonomic classes of microbes automatically&nbsp;from standard 16S rRNA profiles, is used to uncover actionable patterns driving developmental fate in early life. Here we publish the key qnet models to accompany our upcoming publication.</p>