MBI Institute Partner: University of Notre Dame
Contact: Steve Buechler
The Interdisciplinary Center for the Study of Biocomplexity
Department of Mathematics
There is a strong group of researchers in the area of Mathematical Biology at the University of Notre Dame. The research activities are associated with the Center for the study of Biocomplexity, headed by Professor Mark Alber as its director. The goal of the center is to meld physical, mathematical, and computational approaches with those of modern biology to understand this complexity in a quantitative and predictive way. The center is devoted to a variety of projects, using a variety of methodology such as Quantitative experimentation, mathematical modeling, and compute simulation. For more information, please visit the website http://www.nd.edu/~icsb/
For information about the department of Mathematics, please visit http://math.nd.edu/
Job Opportunities
Assistant Professor of Disease Ecology and Assistant/Associate Professor of Epidemiology
University of Notre Dame, Notre Dame, Indiana
Assistant Professor of Disease Ecology. The Department of Biological Sciences seeks faculty candidates who use integrative approaches to study mechanisms that influence disease transmission and/or dynamics. Candidates with cross-disciplinary interests in areas of infectious disease ecology including epidemiology, theoretical modeling, ecological processes, or evolutionary pathways that influence disease pathogens or their vectors are encouraged to apply. The successful candidate will be expected to establish a vigorous externally-funded research program that will complement an active interdisciplinary research community with foci in the ecology, evolution, genetics, and functional genomics of pathogens, their insect vectors, and vertebrate hosts. Apply or inquire at: disease9@nd.edu
Assistant/Associate Professor of Epidemiology. The Department of Biological Sciences seeks faculty candidates who use epidemiological approaches to study diseases of importance to global health. The position is at the Associate Professor level but highly qualified applicants at any level will be considered. Applicants who use theoretical modeling or field-based systems to study disease control or transmission for any pathogen or vector that are of concern in lower or middle-income countries are encouraged to apply. The successful candidate would be expected to establish a vigorous externally-funded research program that complements an active interdisciplinary research community focusing on tropical infectious diseases, especially those transmitted by arthropod vectors. Apply or inquire at: epidem9@nd.edu
Both individuals will participate in the broad initiatives of the Eck Institute for Global Health (http://www.nd.edu/~eigh) and contribute to the undergraduate and graduate teaching mission of the department. The department houses state-of-the-art genomics, bioinformatics, and imaging cores, specialized BSL-3 containment laboratories, insect rearing and research facilities, and an AAALAC-accredited animal facility. Information on department and other college faculty and facilities can be found at http://biology.nd.edu and http://science.nd.edu. Opportunities also exist for collaboration with faculty at the adjoining Indiana University School of Medicine-South Bend. Review of applications will commence on 1 November 2009 and continue until suitable candidates are identified. Qualified individuals should send (pdf format requested) a cover letter, curriculum vitae, separate statements of research and teaching interests, and three letters of reference to the email addresses above.
The University of Notre Dame, an international Catholic research university, is an equal opportunity employer.
Projects at The Interdisciplinary Center for the study of Biocomplexity
Integrated Multiscale Modeling and Experimental Study of Thrombus Development: To prevent the loss of blood following a break in blood vessels, components in blood and the vessel wall interact rapidly to form a clot to limit hemorrhage. This hemostatic response is rapid since delayed clotting results in excessive bleeding. Furthermore, the process is regulated, since excessive and inappropriate clotting within a vessel (thrombosis) reduces the patency of blood flow. The biomedical importance of these processes is highlighted by the approximately 900,000 cases of venous thromboembolic disease resulting in approximately 300,000 deaths in the United States each year. The goal of this proposal is to better understand the regulation of thrombus development by addressing the question why a developing thrombus induced by injury to the vessel wall stops growing.
The main goal of this project is to develop and refine a three dimensional multiscale computational model of thrombogenesis to include the Protein C anticoagulant pathway, the fibrinolytic system, and the polymerized fibrin mesh generated by the coagulation system. The hypotheses generated by the model can then be tested in an experimental vascular injury model utilizing intravital, multiphoton microscopy. The high resolution microscopic images will be processed using newly developed algorithms to generate quantitative outputs and metrics of the internal clot structure that can be compared to the predictions of the simulation. To achieve this goal we formed collaboration between Drs. Alber, Xu and Chen (Notre Dame) and Dr. Rosen (Indiana University School of Medicine) with additional support from Dr. Kenneth Mann (University of Vermont) and Dr. Susan Lord (UNC). A key component of the collaborative effort is close integration of the predictive simulations with in vivo venous injury protocols involving multiphoton intravital microscopy.
While, it is impractical to systematically vary the value of multiple hemostatic factors in in vivo experimental systems, such studies could readily be performed in silico using validated computational models of thrombogenesis. Thus, refined simulations of clot development will not only advance our basic understandings of thrombogenesis but likely have significant impact on the development of therapeutic and diagnostic strategies.
This research is supported by the NSF Grant DMS-0800612, Joint DMS/NIGMS Initiative to Support Research in the Area of Mathematical Biology.
- Xu, Z., Chen, N., Shadden, S., Marsden, J.E., Kamocka, M.M., Rosen, E.D., and M.S. Alber, Study of Blood Flow Impact on Growth of Thrombi Using a Multiscale Model, Soft Matter 5, 769-779 (2009).
- Xu, Z., Chen, N., , Kamocka, M.M., Rosen, E.D., and M.S. Alber, Multiscale Model of Thrombus Development, Journal of the Royal Society Interface 5, 705-722 (2008).
- Lushnikov, P.P., Chen, N., and M.S. Alber, Macroscopic dynamics of biological cells interacting via chemotaxis and direct contact, Phys. Rev. E. 78, 061904 (2008).
Combined Computational and Experimental Study of Complex Interactions that Control Bacterial Motility Pattern Development:
Modeling and simulation are becoming very important research tools in environmental microbiology and engineering. The most advanced of these efforts have focused on single levels or scales, e.g., genomic/proteomic, cellular and population. We are developing computational approaches to integrate models from micro-scales to macro-scales in a seamless fashion. Such multiscale models are essential for producing quantitative, predictive simulations of complex bacterial behaviors such as swarming. At the same time, integration between scales will lead to a much deeper understanding of the universal or generic features of biological phenomena and how simultaneous multiscale processes interact.
The long-term goal of this project is to develop a predictive and quantitative 3-dimensional (3D) multiscale modeling environment and computational Toolkit to study bacterial motility pattern development on different surfaces, which is essential to how bacteria function in real environments. Swarming describes a bacterial surface motility where communities of cells rapidly spread over surfaces. Swarm motility represents a community response to external stimuli. How do biological communities process information? Any question of this kind represents a multiscale problem where individuals sense information and act but it is poorly understood how these interactions are coordinated among large number of cells. Extensive study of this biological problem using predictive simulations involving millions of cells and requiring teraflop computing capabilities, will be a breakthrough in understanding complex natural interactions, connections, complex relations, and interdependencies in biology.
To achieve goals of this project a collaboration has been formed between Mark Alber, Zhiliang Xu, Departments of Mathematics and Physics, Joshua Shrout, Department of Civil Engineering and Geological Sciences, University of Notre Dame, and Matthew Leevy (Senior Personnel), Notre Dame Integrated Imaging Facility.
The ability to understand and predict complex interactions between biological organisms that respond to differences in their chemical and physical environment will transform our understanding of community behavior. P. aeruginosa and other swarming bacteria colonize water distribution systems, agricultural plants and animals, and many medically important surfaces including engineered materials used in joint replacement, medical imaging instruments, contact lenses, and catheters. Prevention of bacterial colonization is a very important method of preventing subsequent transfer and infection to humans.
This research is supported by the NSF Grants DMS-0719895 and CCF-0622940.
- Wu, Y., Jiang, Y., Kaiser, D., and M. Alber, Bacteria perceive distant neighbors via repeated cell-cell contacts, Proc. Natl. Acad. Sci. USA USA 106 4 1222-1227 (2009) (featured in the Nature News, Heidi Ledford, Reversing helps bacterial swarms to spread, January 20th, 2009, doi:10.1038/news.2009.43).
- Wu, Y., Jiang, Y., Kaiser, D., and M. Alber, Social Interactions in Myxobacterial Swarming, PLoS Computational Biology 3 12, e253 (2007).
- Sozinova, O., Y. Jiang, D. Kaiser, and M. Alber, A Three-Dimensional Model of Fruiting Body Formation, Proc. Natl. Acad. Sci. USA 103 No.46, 17255-17259 (2006).
