Systems biology in 3D space--enter the morphome

Systems-based understanding of living organisms depends on acquiring huge datasets from arrays of genes, transcripts, proteins, and lipids. These data, referred to as 'omes', are assembled using 'omics' methodologies. Currently a comprehensive, quantitative view of cellular and organellar systems in 3D space at nanoscale/molecular resolution is missing. We introduce here the term 'morphome' for the distribution of living matter within a 3D biological system, and 'morphomics' for methods of collecting 3D data systematically and quantitatively. A sampling-based approach termed stereology currently provides rapid, precise, and minimally biased morphomics. We propose that stereology solves the 'big data' problem posed by emerging wide-scale electron microscopy (EM) and can establish quantitative links between the newer nanoimaging platforms such as electron tomography, cryo-EM, and correlative microscopy.