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CDI Workshop Titles and Abstracts
Presentation materials: PPT The human cardiovascular system is so complex that it remains unfeasible to numerically simulate its entire function using three-dimensional models. Studying wave propagation in pulsating arteries and local hemodynamics, however, is important in understanding the mechanisms leading to various cardiovascular complications. Many clinical treatments can only be studied in detail if a reliable model describing the response of arterial walls to the pulsatile blood flow is considered. Although fascinating progress has been made in some areas of modeling and simulation of the human cardiovascular system many of the basic difficulties remain open and will continue to present major challenges in the years to come.In an interdisciplinary effort involving mathematicians, cardiologists, and engineers, our group has begun a comprehensive study of fluid-structure interaction between pulsatile blood flow and human arterial walls in healthy and diseased states. The speaker will give an overview of the main problems in this area and show examples of how mathematics, combined with computation, bioengineering, and cardiovascular measurements can shed light on the fundamental difficulties associated with this multi-physics and multi-scale problem. Examples of how this research aided the design of vascular devices called stents and stent-grafts used in nonsurgical treatment of aortic abdominal aneurysm and coronary artery disease will be presented. Experimental measurements performed at our Mock Circulatory Flow Loop assembled at the Texas Heart Institute, will be shown. This is a joint work with Dr. Z. Krajcer and Dr. D. Rosenstrauch (Texas Heart Institute), Dr. C. Hartley (Baylor College of Medicine), Prof. R. Glowinski, Prof. T.W. Pan, Prof. G. Guidoboni (University of Houston), Prof. A. Mikelic (University of Lyon 1, France), and Prof. J. Tambaca (University of Zagreb, Croatia).
In this talk, we argue that answering such questions convincingly is a fundamental challenge for Systems Biology, and report on our recent approaches for addressing these questions. Specifically, we present results that demonstrate how mathematical models can be used to optimally and algorithmically discriminate between alternative, but equally plausible, models of biological networks. We then illustrate, through biological examples, the applicability of these methods and discuss how, in combination with careful systemic analysis, they can help decipher the organizational principles of biological networks. We finally comment on our current and future experimental/mathematical adventures, which are motivated (and necessitated) by the investigation of similar realistic biological problems.
Presentation materials: PDF Intravascular clotting is triggered when damage to the lining of a blood vessel initiates the intertwined processes of platelet aggregation and coagulation. This leads to the formation on the damaged surface of clumps of cells intermixed with a fibrous protein gel. Platelet aggregation begins when circulating blood platelets adhere to the damaged wall. Other platelets, activated by chemicals released by these platelets, bind to the already wall-adherent platelets, thus building a platelet aggregate. Coagulation is itself comprised of two distinct subprocesses. One involves a network of tightly-regulated enzymatic reactions that begins with reactions on the damaged vessel wall and continues with reactions on the surfaces of activated platelets. The final enzyme thrombin i) activates additional platelets and ii) creates monomeric fibrin which polymerizes into the fibrous gel component of the clot. This polymerization process is the second subprocess of coagulation, and it triggers a second enzymatic network, the fibrinolytic system, that begins to degrade the newly formed fibrin gel even as the coagulation system is promoting continued gel formation. These processes all occur in the face of continued blood flow past the injury, and are strongly affected by the fluid dynamics by means that are as yet poorly understood.Pathological clotting (thrombosis) is the immediate cause of most heart attacks and strokes. Consequently it remains the focus of intense experimental investigation, most of which focuses on small component parts of the clotting process. Little research is done into the integrated actions of these parts. The reason for this is clear: the biochemical, biophysical, and biomechanical interactions important in thrombosis are complex; dynamic; spatially distributed; involve disparate physical, mechanical, and chemical processes; and span a wide range of spatial and temporal scales. Understanding these interactions poses severe challenges to traditional laboratory experimentation. Investigating clotting as an integrated system is essential, and this requires tools well suited to looking at the dynamic behavior of complex systems, namely, mathematical modeling and computation. In this talk, I will sketch our efforts at formulating computational models of platelet aggregation that take into account biological as well as physical aspects of the process. I will describe how our modeling of coagulation, with a simple treatment of flow and platelet events, shows how these physical features strongly impact the biochemical system. I will sketch our new explorations into fibrin polymerization and gelation. Lastly, I will outline the work we plan to build computational models of the integrated processes of platelet aggregation, coagulation, fibrin polymerization, and fibrinolysis. This will require an interdisciplinary team of mathematicians, computational scientists, and clotting experimenters working closely with one another, to build realistic models of clotting, develop computational tools that fully exploit the power of new computing systems, and carry out tandem computational and experimental explorations designed from the start to maximally inform one another.
I will describe two projects in my lab on the study of proteins. One is to use sequential Monte Carlo (SMC) and particle filtering method to estimate the side-chain comformational entropy of proteins; the second is on the simulation and optimization of hydrophobic-hydrophilic (HP) protein models. In the second study, we developed a novel fragment-regrowth Monte Carlo procedure, which uses the SMC idea in Markov chain Monte Carlo iterations. When applied to the seven well-known 3-D HP models designed by other researchers, our algorithm gave the best results to-date, some of which are significantly better than the previously known best results.
Biological organization arises via spontaneous, hierarchical self-assembly processes. A principal benefit of current genome projects has been to provide the "parts lists" of components for such processes. The central task of computations in biology today is to determine the underlying principles of biomolecular recognition that enables reconstruction of these components into higher order patterns of organization. In this presentation, I introduce the Potential Distribution Theorem (PDT), which provides a theoretical foundation and a practical tool for developing algorithms to compute conformational free energies associated with these biomolecular recognition events. I will describe two research efforts aimed at implementing the PDT to elucidate the molecular basis for selectivity in the KcsA potassium ion channel, and for sensitivity to peptide-specific signals delivered through the T-cell receptor/peptide-major histocompatibility complex that can lead to T-cell activation in adaptive immune response.
Presentation materials: PDF To better "understand Complexity in Natural, Built, and Social Systems," the Cyber-Enabled Discovery and Innovation initiative seeks proposals that integrate meathematical modeling, computational thinking, and algorithmatical advances. This talk will describe statistical tools for more effectively integrating knowledge gained from computational research with physical experiments. An example drawn from bioengineering will be used illustrate the main points. |
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