A complex adaptive system depends on cause-and-effect relationships at every scale. Patterns inherent in complex adaptive systems require special modes of description. For example, the flocking patterns of birds are observed at the 'many bird' level but are the result of the forces and uncertainties that shape the behaviors of individual birds - which are in-turn shaped by numerous constraints imposed by the environment.  Complex adaptive systems cannot be accurately described using 'reductionism', and instead require specialized methods that integrate multi-scale information. 

In mammals, sperm outnumber eggs by many millions to one. Sperm are capable of finding and fertilizing an egg in a range of microenvironments. They are able to do this despite not sharing pairwise information the way somatic cells do through cell-to-cell networks (e.g., neurons in the brain). We are investigating how sperm collectively compute via parallel execution of stochastic searches to better understand the fundamental principles that enable complex tissues to form and maintain stability in the face of environmental uncertainty.

Read our Paper on Sperm Redox Transitions

Read Our Paper on Systems Biology of Sperm Search 

Read Our Paper on Optimal Random Search on Confined Domains

Sperm and other motile cells are much more challenging to image than adherent somatic cells. Computer aided sperm motility analysis has not changed much since its advent in the 1980's. Rudimentary acquisition and analysis methods have limited the understanding of how sperm collectively search for an egg. Our collaborative efforts with Dr. David Hart at ECU are focused on building AI methods for tracking sperm over physiologically relevant timescales at the high cell densities characteristic of undiluted semen samples. 

Read Our Paper on Sperm Specific Tracking Metrics

New Paper Coming Soon: Closed Loop Data Engine for High Density Cell Tracking Over Long Trajectories!!

Sperm must move in a way that increases the probability of egg contact using their flagella. Protozoans must forage for food. Microswimmers don't actually 'swim', but instead do something more like crawling. This is because inertia plays essentially no role in movement at small scales. Through our collaborations with Dr. Martin Bier at ECU, we are working to understand how variation in speed at short timescales produces long timescale pattern transitions that enable microswimmers to optimize movement for energy efficiency. 

New Paper Coming Soon: Efficiency of Biflagellate Microswimmers

Tissues are comprised of many millions of cells. Though cells have been historically treated as though they are simple and uniform, we now know that they are unique and heterogeneous, how this apparent variation influences the formation and stability of tissues remains a mystery. In collaboration with Dr. Paul Vos at ECU we are using statistical methods with time-lapse spectral flow cytometry and microscopy to model the cell population scale dynamics of capacitating sperm and synciating myoblasts.

Read our Preprint on Compositional Analysis of Sperm Subpopulations

New Paper Coming Soon: Compositional Analysis of Mouse Myoblasts During In Vitro Synciation.

ECU Biology and the Eastern Region Pharma Training Center in Greenville, NC