Tarynn M. Witten, Ph.D., MSW, FGSA
| Center for the Study of Biological Complexity
VCU Life Sciences, Suite 111
1000 West Cary Street
| Tel: 804-827-7371
| Web: www.people.vcu.edu/~tmwitten/
High performance and multi-scale computational and mathematical
algorithms and modeling in molecular biology, genetics, cancer,
aging and complexity.
| BBSI Philosophy: Read my philosophy concerning your BBSI experience.
| BBSI Simulations: 2004   2005 2006 2007 2008 2009
| Video Link: Click Here
BBSI Project 1: The Virtual Parasite Project
Link to Virtual Parasite Project Site
Infectious diseases, in spite of antibiotic and other treatments, remain one of the biggest medical problems to date. The overall problem of understanding host-parasite dynamics is extremely important, as it is intrinsic to the study of infection at all organismal scales. Many examples of such host-parasite systems exist, with debilitating and/or fatal consequences for humans all over the planet; malaria, schistosomiasis, and Chagas’ Disease, for example. Because of its complex life-cycle, T. cruzi provides one of the most fascinating and complex, yet sophisticated initial model systems for investigation. Our methodology is based upon an integrated mathematical, in silico modeling approach that is directly coupled to biological experimentation. The long-term goal of this project is to apply novel mathematical and computational modeling technologies, well informed by biological experimentation, to specific host-parasite systems in order to develop new paradigms for understanding the infectious disease process, for the purpose of developing new therapeutic and public health interventions and strategies. Towards these goals, we are developing and will make available to the scientific community an extensible, portable, in silico, multi-scale, high performance computational model of parasite-host dynamics and use that model to study effective strategies for managing the host-vector and parasite dynamics of the T. cruzi parasite, the causal agent in Chagas’ Disease. This modular environment will allow other users to create "parasite modules" for such parasites and microbes as E. histolytica and the potential bioterrorism agents like C. parvum (for which there is no treatment). Students will be involved in high performance computing models of host-parasite dynamics and will have the opportunity to do associated laboratory work as well.
Read even more about the VPP
BBSI Project 2: Modeling and Simulation of the Aging-Cancer Interface
In humans, the incidence of cancer rises exponentially in the final decades of life, culminating in a lifetime risk of 1 in 2 for men and 1 in 3 for women. This dramatic age-dependent escalation in cancer risk is fuelled largely by a marked increase in epithelial carcinomas from ages 40 to 80 years. By the year 2030, projects indicate that the total of all new cases of cancer in the USA will be 2.1 million. 1.5 million in patients over the age of 65 and 0.5 million in patients over the age of 80. In addition to the increased risk is the fact that the most rapidly growing portion of the US population is those over 85 years old. What underlies this intimate link between cancer and aging? In this project, students will investigate mathematical and computer simulation models of aging and cancer and will assist in developing a biologically accurate and biomedically relevant computer model of the aging-cancer process.
BBSI Project 3: Modeling the Dynamics of Fibromyalgia
Fibromyalgia (FM) is a rheumatic disorder characterized by chronic widespread musculoskeletal pain and tenderness in the absence of well-defined musculoskeletal or rheumatic disease. The finding of tenderness in 11 of 18 specified soft tissue points on digital palpation confirms this diagnosis. In addition to pain and tenderness, patients often present with fatigue, insomnia, cognitive difficulty and gastrointestinal complaints. FM patients present with a wide range of symptom fluctuations and high levels of comorbidity and are met clinically with an absence of curative interventions. FM is a condition that affects more women than men with approximately 3,400 women and 500 men/100,000 and increases with age to more than 7% in women. No single etiological factor has yet been identified. The purpose of this project is to develop a mathematical model of the molecular dynamics of fibromyalgia. Students will work of various applications of mathematical modeling and computer simulation in order to develop a biologically accurate and biomedically relevant model of the fibromyalgia dynamics.
BBSI Project 4: Signal Processing and Biological Complexity
Many living system processes can be measured and the subsequent measurements treated as a biological signal of sorts. In this project, students will be working with a number of VCU faculty on the analysis of a set of biological signals taken in an experimental design meant to study the effects of massive blood loss in a trauma scenario such as the battlefield or during post-operative recovery from a massive accident. Students will learn how to analyze signals and be responsible for independent analysis of data from this project.
BBSI Project 5: Simulation and Mathematical Modeling of Cellular, Metabolic and Macro-Physiological Processes
Over the past decade, bioinformatics data and biomedical engineering data has provided a strong underpinning for sophisticated modeling and simulation of genetic and cellular metabolic and macro-physiological processes. In this project, students will choose among a number of modeling and simulation problems arising in the above fields. Students will work on various aspects of computer simulation and mathematical modeling and will obtain experience in the complexities of trying to accurately model the behaviors of living systems.
BBSI Project 6: Data Sonification
Scientific visualization of complex data has become a discipline in and of itself. Visualization can be found in all areas of computational biomedicine and bioengineering. While the eye allows us to discern differences in data, very little work has been done in data sonification/audification; the use of sound to understand complex datasets. Moreover, little work has been done in coupling data sonification with scientific visualization. In this project, students will be involved in developing different ways, using both sound and sight, to interact with complex datasets arising in bioinformatics and bioengineering.
BBSI Project 7: Visualization Of Complex Biomedical Engineering and Bioinformatics Datasets
In this project, students will investigate different ways of representing complex datasets where, by complex, we mean datasets that contain more than 5-dimensions or variables of interest. Students will be involved in the development of new methods for visualizing such datasets along with developing new bio-user-friendly interfaces.
BBSI Project 8: Modeling Replicative Senescence
Human cells in cell culture have a limited proliferative capacity. After a period of vigorous proliferation, the rate of cell division declines and a number of changes occur in the cells including increases in size, in secondary lysosomes and residual bodies, nuclear changes and a number of changes in gene expression which provide biomarkers for senescence. Although human cells in culture have been used for over 40 years as models for understanding the cellular basis of aging, the relationship between replicative aging to aging of the organism is still not clear. In this project, students will be involved in mathematical modeling and computer simulation of cellular senescence processes including the modeling of the signal transduction pathway activated by receptors with tyrosine kinase activity. Students will engage in modeling apoptotic pathways and cell stress pathways. Models of telomere dynamics will also be constructed.
BBSI Project 9: Computational Models of Esophageal Cancer Progression
Esophageal cancer is the sixth most common malignant neoplasm in the world. Every year, approximately 13,900 Americans are diagnosed with esophageal cancer and 13,000 die from it. Patients with esophageal cancer generally present progressive dysphagia, malnutrition and weight loss. There have been significant improvements in the treatment options for patients with esophageal cancer, including chemotherapy, radiotherapy, surgical resection, endoscopic mucosal resection (EMR) or multimodality therapy. As with other malignant tumors, accurate TNM staging and localization of the esophageal cancer are important parameters for selection of the optimal treatment and prediction of patients’ prognoses. Patients with limited disease progression or those with early-stage tumors can obtain good prognoses by complete surgical resection or chemoradiotherapy. On the other hand, patients with advanced-stage cancer have poor prognoses even if aggressive surgical resection is performed. Students working on this project will develop a 3D high performance mathematical and computational model of esophageal cancer progression using both anatomically accurate as well as approximate cellular automata models. Depending upon scheduling, arrangements will be made for students to spend time at the Massey Cancer Center and other cancer biology and treatment laboratories.
Other research interests
Biomathematics/Mathematical Biology, Complexity of Biological Systems,
Mathematical Modeling, Aging, Gerontology, Geriatrics, Applied Mathematics,
Computer Simulation, Partial Differential Equations, Computer Music, Phenomenology