This special focus is jointly sponsored by the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), the Biological, Mathematical, and Physical Sciences Interfaces Institute for Quantitative Biology (BioMaPS), and the Rutgers Center for Molecular Biophysics and Biophysical Chemistry (MB Center). This meeting is also sponsored by The Center for the Development of a Virtual Tumor (CViT), and The National Cancer Institute's Integrated Cancer Biology Program.
Computational methods are coming to have intriguing roles in the analysis of diseases such as cancer, for example in understanding how genetic mutations affect multicellular behavior or how spatial-temporal patterns of angiogenesis impact the efficacy of cancer therapies. Due to the inherent non-linearity and complexity of the many networked physiological processes involved on the cellular level alone, conventional reductionism-driven approaches fail in providing answers to such questions. Given the multi-scaled patho-physiology involved, it is becoming abundantly clear that cancer research requires a cross-disciplinary, complex, systems science approach, in which innovative multi-scaled computational cancer models play a central role. Ultimately, these "systems biology" models will allow cancer researchers to properly study such critical, interconnected tumorigenesis processes as initiation, progression, invasion, angiogenesis and metastasis. The potential applications for algorithms that capture these processes therefore range from experimental and clinical cancer research, such as treatment outcome predictions, to virtual trials for the pharmaceutical industry. This workshop will present a variety of relevant computational tumor models and algorithms, covering several scales of interest by starting from the genetic instability and the functional genomics level up to tumor cell invasion and the angiogenesis level. Work on tumor cell signaling and information processing, multicellular pattern formation and scaling laws will be discussed as well. Finally, the workshop will also focus on several key challenges related to cancer modeling, such as biomedical data acquisition, access and quality, as well as the pros and cons of combining different (e.g., discrete and continuous) modeling approaches.
The Computational Tumor Modeling Working Group is part of The National Cancer Institute's Integrative Cancer Biology Program, a new initiative in systems biology. The goal of this initiative is to promote the analysis of cancer as a complex biological system, with the ultimate goal of developing reliably predictive computational models of various cancer processes, facilitating the development of cancer interventions. This will be achieved through the integration of experimental and computational approaches towards the understanding of cancer biology. One way of achieving this goal is for the National Cancer Institute to sponsor a series of Workshops that bring together cancer biologists and scientists from fields such as mathematics, physics, information technology, imaging sciences, and computer science.
This Computational Tumor Biology Working Group at DIMACS will bring together scientists who are already working in the highly interdisciplinary field of mathematical and computational cancer modeling and simulation as well as "newcomers" who are interested in this exciting research area. The workshop's main goal is to introduce and discuss innovative concepts, algorithms and platforms and to establish new cross-disciplinary collaborations. The focus will be on multiscale modeling as well as on data integration and visualization techniques, i.e. on the challenging interface between experiment and theory. The workshop is also intended to introduce the Center for the Development of a Virtual Tumor (CViT), one of the National Cancer Institute's funded Integrative Cancer Biology Programs. CViT's long term aim is to develop a module-based toolkit for cancer research.