This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator. Apoptosis is one of the major processes that need to be clarified/researched in the post-genomic era. It has relevance on cancer research, viruses, neurodegenerative diseases, and military applications such as ionizing radiation exposure, for example. In our view it is one of the most important cellular processes whose complete understanding (and manipulation) can have a huge impact on many of the health related areas. It could provide cures for cancer, tools to deal with viruses, and a huge impact in gerontology: such as tools to fight Parkinson's, Alzheimer's disease, and other brain disease. The simulation method proposed is discrete as opposed to the continuous simulation techniques such as ordinary differential equation (ODE) methods and also much faster than Monte-Carlo simulations such as Gillespie's algorithm (also discrete, but much slower than our method: by a factor of about 60 times slower for one run, typically one would need at least 20 runs for an accurate prediction for a specific minority of cells). The mentor and mentee both have a common interest in the process of cellular death known as apoptosis: the mentor from the perspective of neuronal cell and tissue engineering and the mentee from the perspective of computational systems and modeling. The most recent publications of these two scientists illustrate the point. From Dr. DeCoster: 'The Nuclear Area Factor (NAF): a measure for cell apoptosis using microscopy and image analysis' (2007) and from Dr. Paun: 'Simulating FAS-induced apoptosis by using P systems' (2007). Both Drs. DeCoster and Paun in addition to their respective program affiliations at Louisiana Tech are also associated with the Institute of Micromanufacturing (IFM), which is providing an additional common ground for collaboration and the development of model test systems. In the past 6 months, Drs. DeCoster and Paun have been discussing and sharing data to target potential collaborative areas of research as well as serving on one of each other's student Ph.D. thesis committees. One of Dr. Paun's Ph.D. students is currently enrolled in Dr. DeCoster's graduate course: BIEN 557-'Neural Cell Measurement Methods'. This LBRN program would provide a formal mechanism for the collaborative venture of bringing together biological and computational systems for a better understanding of the cellular death process of apoptosis targeted in different directions (the brain, viruses, cancer, etc). This project would also include a mentor from LSUHSC Shreveport (Dr. James Cardelli), to provide insight and guidance for cancer research questions of basic science and clinical relevance. A goal of this mentored collaboration project is to develop computational systems for modeling and thus better understanding the process of cell apoptosis using biochemical pathway assays and digital image-based data. It is anticipated that three major outcomes will result from this partnership: 1) enhanced scientist mentoring; 2) increased basic research knowledge; and 3) increase of the biomedical knowledge on campus through the inclusion of research results in the teaching of senior undergraduate/graduate courses.
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