Macrobiology

The redundancy and pleiomorphy of most physiologies implies any single set of processes and genes are unlikely to capture the entirety of the physiology operating in all contexts. Models of physiology that are defined from the bottom-up do not work very well for this reason, even if the mountains of data required to define these models are obtained. Also, purely statistical or data driven perspectives fail to capitalize on the enormous trove of prior knowledge gleaned in the biological sciences. Macrobiology leverages this prior knowledge in the interpretation of whole physiologies (and pathologies) using empiircal grounding offered by high-throughput, comprehensive measurements.

Applications

Developmental Signature in Cancer: The remarkable recapitulation of embryogenesis in oncogenesis has been recognized for over a century. A macrobiology approach has allowed futher characterizaton of these parallels and use them for highly robust human prognoses in cancer. It has also allowed a more robust re-categorization into an early developmental (notable for cell cycle activitiy) class and inflammatory/late developmental (cell-cell signaling, innate immunity) class.

Localized Genomic Regulation: Most research of the regulatory control of genes assume a wide-ranging free-for-all across the entire genome. A macrobiology approach reveals subtle but reproducible evidence of highly localized control in the chromosomal neighborhood of the controlling elements (i.e microRNA). Another example of global control through local action.

A Comprehensive View of Dysregulation in Diabetes: Inidividual mouse models, human population studies, the study of individual signalling pathways, or even whole transcriptome expression studies do not embrace the full multi-organ multidisorder that this growing health threat consitutes. By triangulating across multiple measurement modalities we have characterized a much broader set of disordered physiologies than reported in prior single studies.

Reclassifying Human Disease: The current classification of human disease now reflects organ or insittutional boundaries rather than shared or distinguishing physiologies. By sampling genome-scale measurements across all available tissues and pathophysiologies, we have taken the first steps towards a macrobiology-evidenced nosology of human pathophysiology.

Research Collaborations

Computational Genomics Lab at Boston University

Informatics for Integrating Biology to the Bedside: A National Center for Biomedical Computing