Current Research
High Throughput Biotechnology
Microarrays employ the properties of DNA hybridization to monitor global changes in gene expression (i.e. the "expression level" of every gene in a genome). Each "spot" on a microarray is composed of DNA molecules (probes) that are designed to hybridize uniquely to one genic sequence (target). However, no probe sequence binds its target exclusively: the unintentional binding is denoted cross hybridization and affects both the sensitivity and selectivity of each probe and the sensor overall. Using data-mining and modeling approaches, we are investigating the effects of cross hybridization to create more precise and specific microarray technologies. Click here for more!
Receptor-Mediated Adhesion
Platelets - the cells that initiate and mediate clotting and thrombosis - are among the most populous cells in the bloodstream with a concentration of 3x1011 cells/liter. Platelet adhesion to the arterial or venous wall is mediated by interactions of cell-membrane-bound glycoproteins such as GPIba with complementary biomolecules such as vwf, which are bound to the endothelium. In 'small systems' such as the contact area between cells where such interactions occur, single-molecule events on the nanoscale translate to macroscopic phenomena, such as adhesion or the passage of current across neurons. Thus, measurement of the kinetics of such events requires a stochastic approach, insofar as rates of complex formation or macromolecular transformation cannot be measured by conventional chemical means. We are employing our expertise in this area in collaboration with Tom Diacovo in the pathology department at Columbia University to quantify the kinetics of dissociation of blood cell adhesion receptors from their targets and characterize the effects of mutation and biochemical disruption on the adhesive properties of blood cells. Please see the papers page for more information.
Systems Biology
In a given moment of the life of a cell, only a handful of key molecules may be present whereas others may be abundant. That is, the populations of biochemical species may vary over orders of magnitude. Furthermore, the intrinsic rates of chemical association, dissociation and conversion of these species may vary considerably. Therefore, (a) randomness may be manifested in the kinetic time evolution of some biological processes and (b) mathematical descriptions of said processes may be "stiff" due to disparate timescales, and thereby recalcitrant to numerical integration. Dr. Laurenzi is developing chemical models for the kinetics and mechanisms of the vast number of interactions between proteins, DNA, and RNA for use in "stochastic simulation". Unlike molecular simulations such as GCMC and MD, these simulations track the time-evolution of biochemical populations over time, and explicitly account for the effects of "small number statistics". This "in-silico" approach is currently being applied to systems as diverse as gene expression and central metabolism in the baker's yeast S cerevisiae.
Multi-component aggregation-fragmentation phenomena
Due to the mathematical complexity of the traditional deterministic approach to aggregation kinetics, the exact quantification of the time-evolution of batch (constant-volume, spatially-invariant) aggregation-fragmentation processes such as blood coagulation and branched polymerization has been exceedingly difficult to predict. Dr. Laurenzi has developed an algorithm to predict the exact kinetic time evolution of particle aggregation and breakup in systems featuring multiple conservation laws or chemical or biological components. He is applying these techniques to quantify the physical criteria for gelation/precipitation of antibodies with their antigens, blood fibrinogen and blood platelets, and other biological coagulation processes. Please see the papers page for more information.
