#6 · Systems biology

Models couple longitudinal microbiome data to temporal dynamics and process endpoints

The dominant thread in this set is computational modeling of microbial community structure and function, most directly represented by CoDaLoMic, a published R package for longitudinal compositional microbiome data that captures group-level taxa interactions and temporal dynamics. Its distinguishing feature is joint treatment of compositionality and time, which the other items do not address. The remaining items are related but distinct: a long-read syntenic pangenome of 312 Gardnerella genomes resolving 21 lineages, with cryptic plasmids and virulence and metabolic stratification; a label-free single-cell morphology and Raman workflow with ML species identification for selective culturing; and a genome-scale metabolic model atlas of over 3000 Streptococcus suis strains. These do not model longitudinal data. What is new here is the statistical framework for longitudinal compositional microbiome data, not the genomic or metabolic resources.