Systems Biology Levels Up: Modeling Multi-scale Processes
Posted April 06, 2010
To a systems biologist, the patterns that occur throughout biology are mathematically tractable; the field's principal goal is to discover their underlying equations and make testable predictions from them. But while overall patterns are easy to see, the mechanisms driving their establishment and growth are not. Worse, these mechanisms operate at length scales that span ten orders of magnitude—from submicroscopic DNA molecules to whole ecosystems—and time scales just as large.
At the January 14, 2010, meeting of the Academy's Systems Biology Discussion Group three leading systems biologists presented their latest work on multi-scale problems. Ned Wingreen discussed his team's work on a deceptively simple-looking biological process: chemotaxis in the bacterium E. coli. Alexander Anderson takes a minimal modeling approach to try to understand the underlying rules governing tumor growth. And Jeremy Rice is working on long QT syndrome, a rare but serious congenital heart condition that can cause arrhythmia and sudden death in otherwise healthy people.
Use the tabs above to find a meeting report and multimedia from this event.
Endres RG, Oleksiuk O, Hansen CH, et al. 2008. Variable sizes of Escherichia coli chemoreceptor signaling teams. Mol. Syst. Biol. 4: 211. Full Text
Endres RG, Wingreen NS. 2006. Precise adaptation in chemotaxis through "assistance neighborhoods." Proc. Natl. Acad. Sci. USA 103: 13040-13044. Full Text
Keymer JE, Endres RG, Skoge M, Wingreen NS. 2006. Chemosensing in Escherichia coli: two regimes of two-state receptors. Proc. Natl. Acad. Sci. USA 103: 1786-1791. Full Text
Anderson ARA, Hassanein M, Branch KM, et al. 2009. Microenvironmental independence associated with tumor progression. Cancer Res. 69: 8797-8806.
Enderling H, Anderson ARA, Chaplain MAJ, et al. 2009. Paradoxical dependencies of tumor dormancy and progression on basic cell kinetics. Cancer Res. 69: 8814-8821.
Kam Y, Karperien A, Weidow B, et al. 2009. Nest expansion assay: a cancer systems biology approach to in vitro invasion measurements. BMC Res. Notes 2:130. Full Text
Reumann M, Fitch BG, Rayshubskiy A, et al. 2009. Strong scaling and speedup to 16,384 processors in cardiac electro-mechanical simulations. Conf. Proc. IEEE Eng. Med. Biol. Soc. 1: 2795-2798.
Reumann M, Fitch BG, Rayshubskiy A, et al. 2009. Orthogonal recursive bisection data decomposition for high performance computing in cardiac model simulations: Dependence on anatomical geometry. Conf. Proc. IEEE Eng. Med. Biol. Soc. 1: 2799-2802.
Reumann M, Fitch BG, Rayshubskiy A, et al. 2008. Large scale cardiac modeling on the Blue Gene supercomputer. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2008: 577-580.
Ned S. Wingreen, PhD
Ned Wingreen received his PhD in theoretical condensed matter physics from Cornell University in 1989. He did his postdoc in mesoscopic physics at MIT before moving, in 1991, to the newly founded NEC Research Institute in Princeton. At NEC, he continued to work in mesoscopic physics, but also started research on the statistical mechanics of protein folding. Thinking about proteins led him inexorably down the path into biology. During a sabbatical at UC Berkeley in 1999, his primary focus shifted to systems biology of bacteria. Wingreen joined Princeton University as a professor of molecular biology in 2004, with a joint appointment in the Lewis-Sigler Institute as of 2008. Wingreen's current research focuses on modeling intracellular networks in bacteria.
Alexander R. A. Anderson, PhD
Alexander R. A. Anderson is co-director of the Integrated Mathematical Oncology (IMO) department and senior member at Moffitt Cancer Center. Anderson performed his doctoral work on hybrid mathematical models of nematode movement in heterogeneous environments at the Scottish Crop Research Institute in Dundee, UK. His postdoctoral work was on hybrid models of tumor-induced angiogenesis with Mark Chaplain at Bath University, UK. He moved back to Dundee in 1996 where he worked for the next 12 years on developing mathematical models of many different aspects of tumor progression and treatment, including anti-angiogenesis, radiotherapy, tumor invasion, evolution of aggressive phenotypes and the role of the microenvironment. He is widely recognized as one of only a handful of mathematical oncologists that develop truly integrative models that directly impact upon biological experimentation. His pioneering work using evolutionary hybrid cellular automata models has led to new insights into the role of the tumor microenvironment in driving tumor progression. Due to his belief in the crucial role of mathematical models in cancer research he moved his group to the Moffitt Cancer Center in 2008 to establish the Integrated Mathematical Oncology department.
John Jeremy Rice, PhD
John Jeremy Rice is a research staff member at the Center for Computational Biology at IBM's Thomas J. Watson Research Center. He is a member of the Functional Genomics and Systems Biology Group and seeks to merge computational simulation with emerging technologies in genomics and proteomics. He is currently working on methods to infer cellular signaling pathways from high-throughput data. He has published extensively in the field of cardiac physiology simulation, including models of electrophysiology, calcium signaling and muscle contraction. This work continues from his PhD thesis work at the Department of Biomedical Engineering of The Johns Hopkins University from which he graduated in 1998. He is currently an adjunct faculty member of the same department and teaches undergraduate and graduate courses in modeling and physiology.