Computational Morphodynamics and Systems Biology

 

 

A computational morphodynamics study starts with researchers extracting cell geometry and topology information to create a mechanical cellular template from biological images. Data from genetic, biochemical, cellular, and molecular biology experiments, along with imaging studies, help infer the biochemical networks that control developmental signaling. The model is designed so that the biochemical network within each cell directs interactions between cells.

Previously, we identified a set of genes called the ABC genes, whose overlapping expression determines the identity of the floral organs in different regions of a flower.

Systems biology aims to integrate large-scale datasets from genomics, gene expression, proteomics, metabolomics, and imaging studies into a comprehensive framework to explain cellular and organismal functions. Computational morphodynamics has emerged to elucidate the complex temporal and spatial interactions of growth and signaling through computational modeling integrated with biological imaging.